AuthorWithPapers

A Semantic Scholar author record with paper list
AcademicResearchPapersCitationsAuthorsScientific LiteratureAIRecommendations
Properties

Name	Type	Description
authorId	string	Semantic Scholar’s unique ID for the author.
externalIds	object	An object that contains the ORCID/DBLP IDs for the author, if known.
url	string	URL of the author on the Semantic Scholar website.
name	string	Author’s name.
affiliations	array	Array of organizational affiliations for the author.
homepage	string	The author’s homepage.
paperCount	string	The author's total publications count.
citationCount	string	The author's total citations count.
hIndex	string	The author’s h-index, which is a measure of the productivity and citation impact of the author’s publications: https://www.semanticscholar.org/faq#h-index
papers	array
View JSON Schema on GitHub
JSON Schema

{
  "$schema": "http://json-schema.org/draft-07/schema#",
  "title": "AuthorWithPapers",
  "description": "A Semantic Scholar author record with paper list",
  "$id": "https://raw.githubusercontent.com/api-evangelist/semantic-scholar/refs/heads/main/json-schema/semantic-scholar-author.json",
  "properties": {
    "authorId": {
      "type": "string",
      "title": "This field will be provided if no fields are specified",
      "description": "Semantic Scholar\u2019s unique ID for the author.",
      "example": "1741101"
    },
    "externalIds": {
      "type": "object",
      "description": "An object that contains the ORCID/DBLP IDs for the author, if known.",
      "example": {
        "DBLP": [
          123
        ]
      }
    },
    "url": {
      "type": "string",
      "description": "URL of the author on the Semantic Scholar website.",
      "example": "https://www.semanticscholar.org/author/1741101"
    },
    "name": {
      "type": "string",
      "title": "This field will be provided if no fields are specified",
      "description": "Author\u2019s name.",
      "example": "Oren Etzioni"
    },
    "affiliations": {
      "type": "array",
      "description": "Array of organizational affiliations for the author.",
      "example": [
        "Allen Institute for AI"
      ],
      "items": {
        "type": "string"
      }
    },
    "homepage": {
      "type": "string",
      "description": "The author\u2019s homepage.",
      "example": "https://allenai.org/"
    },
    "paperCount": {
      "type": "string",
      "description": "The author's total publications count.",
      "example": 10
    },
    "citationCount": {
      "type": "string",
      "description": "The author's total citations count.",
      "example": 50
    },
    "hIndex": {
      "type": "string",
      "description": "The author\u2019s h-index, which is a measure of the productivity and citation impact of the author\u2019s publications: https://www.semanticscholar.org/faq#h-index",
      "example": 5
    },
    "papers": {
      "type": "array",
      "items": {
        "title": "Paper Info",
        "allOf": [
          {
            "$ref": "#/definitions/BasePaper"
          }
        ]
      }
    }
  },
  "type": "object",
  "definitions": {
    "Error404": {
      "properties": {
        "error": {
          "type": "string",
          "description": "Depending on the case, error message may be any of these:\n<ul>\n    <li><code>\"Paper/Author/Object not found\"</code></li>\n    <li><code>\"Paper/Author/Object with id ### not found\"</code></li>\n</ul>",
          "example": "Requested object not found"
        }
      },
      "type": "object"
    },
    "Error400": {
      "properties": {
        "error": {
          "type": "string",
          "description": "Depending on the case, error message may be any of these:\n<ul>\n    <li><code>\"Unrecognized or unsupported fields: [bad1, bad2, etc...]\"</code></li>\n    <li><code>\"Unacceptable query params: [badK1=badV1, badK2=badV2, etc...}]\"</code></li>\n    <li><code>\"Response would exceed maximum size....\"</code></li>\n        <ul><li>This error will occur when the response exceeds 10 MB. Suggestions to either break the request into smaller batches, or make use of the limit and offset features will be presented.</li></ul>\n    <li>A custom message string</li></ul>",
          "example": "Unrecognized or unsupported fields: [author.creditCardNumber, garbage]"
        }
      },
      "type": "object"
    },
    "FullPaper": {
      "properties": {
        "paperId": {
          "type": "string",
          "description": "Semantic Scholar\u2019s primary unique identifier for a paper.",
          "example": "5c5751d45e298cea054f32b392c12c61027d2fe7"
        },
        "corpusId": {
          "type": "integer",
          "description": "Semantic Scholar\u2019s secondary unique identifier for a paper.",
          "example": 215416146
        },
        "externalIds": {
          "type": "object",
          "description": "An object that contains the paper\u2019s unique identifiers in external sources. The external sources are limited to: ArXiv, MAG, ACL, PubMed, Medline, PubMedCentral, DBLP, and DOI.",
          "example": {
            "MAG": "3015453090",
            "DBLP": "conf/acl/LoWNKW20",
            "ACL": "2020.acl-main.447",
            "DOI": "10.18653/V1/2020.ACL-MAIN.447",
            "CorpusId": 215416146
          }
        },
        "url": {
          "type": "string",
          "description": "URL of the paper on the Semantic Scholar website.",
          "example": "https://www.semanticscholar.org/paper/5c5751d45e298cea054f32b392c12c61027d2fe7"
        },
        "title": {
          "type": "string",
          "description": "Title of the paper.",
          "example": "Construction of the Literature Graph in Semantic Scholar"
        },
        "abstract": {
          "type": "string",
          "description": "The paper's abstract. Note that due to legal reasons, this may be missing even if we display an abstract on the website.",
          "example": "We describe a deployed scalable system for organizing published scientific literature into a heterogeneous graph to facilitate algorithmic manipulation and discovery."
        },
        "venue": {
          "type": "string",
          "description": "The name of the paper\u2019s publication venue.",
          "example": "Annual Meeting of the Association for Computational Linguistics"
        },
        "publicationVenue": {
          "type": "object",
          "description": "An object that contains the following information about the journal or conference in which this paper was published: id (the venue\u2019s unique ID), name (the venue\u2019s name), type (the type of venue), alternate_names (an array of alternate names for the venue), and url (the venue\u2019s website).",
          "example": {
            "id": "1e33b3be-b2ab-46e9-96e8-d4eb4bad6e44",
            "name": "Annual Meeting of the Association for Computational Linguistics",
            "type": "conference",
            "alternate_names": [
              "Annu Meet Assoc Comput Linguistics",
              "Meeting of the Association for Computational Linguistics",
              "ACL",
              "Meet Assoc Comput Linguistics"
            ],
            "url": "https://www.aclweb.org/anthology/venues/acl/"
          }
        },
        "year": {
          "type": "integer",
          "description": "The year the paper was published.",
          "example": 1997
        },
        "referenceCount": {
          "type": "integer",
          "description": "The total number of papers this paper references.",
          "example": 59
        },
        "citationCount": {
          "type": "integer",
          "description": "The total number of papers that references this paper.",
          "example": 453
        },
        "influentialCitationCount": {
          "type": "integer",
          "description": "A subset of the citation count, where the cited publication has a significant impact on the citing publication. Determined by Semantic Scholar\u2019s algorithm: https://www.semanticscholar.org/faq#influential-citations.",
          "example": 90
        },
        "isOpenAccess": {
          "type": "boolean",
          "description": "Whether the paper is open access. More information here: https://www.openaccess.nl/en/what-is-open-access.",
          "example": true
        },
        "openAccessPdf": {
          "type": "object",
          "description": "An object that contains the following parameters: url (a link to the paper\u2019s PDF), status (the type of open access https://en.wikipedia.org/wiki/Open_access#Colour_naming_system), the paper's license, and a legal disclaimer.",
          "example": {
            "url": "https://www.aclweb.org/anthology/2020.acl-main.447.pdf",
            "status": "HYBRID",
            "license": "CCBY",
            "disclaimer": "Notice: This snippet is extracted from the open access paper or abstract available at https://aclanthology.org/2020.acl-main.447, which is subject to the license by the author or copyright owner provided with this content. Please go to the source to verify the license and copyright information for your use."
          }
        },
        "fieldsOfStudy": {
          "type": "array",
          "description": "A list of the paper\u2019s high-level academic categories from external sources. The possible fields are: Computer Science, Medicine, Chemistry, Biology, Materials Science, Physics, Geology, Psychology, Art, History, Geography, Sociology, Business, Political Science, Economics, Philosophy, Mathematics, Engineering, Environmental Science, Agricultural and Food Sciences, Education, Law, and Linguistics.",
          "example": [
            "Computer Science"
          ],
          "items": {
            "type": "string"
          }
        },
        "s2FieldsOfStudy": {
          "type": "array",
          "description": "An array of objects. Each object contains the following parameters: category (a field of study. The possible fields are the same as in fieldsOfStudy), and source (specifies whether the category was classified by Semantic Scholar or by an external source. More information on how Semantic Scholar classifies papers https://medium.com/ai2-blog/announcing-s2fos-an-open-source-academic-field-of-study-classifier-9d2f641949e5)",
          "example": [
            {
              "category": "Computer Science",
              "source": "external"
            },
            {
              "category": "Computer Science",
              "source": "s2-fos-model"
            },
            {
              "category": "Mathematics",
              "source": "s2-fos-model"
            }
          ],
          "items": {
            "type": "object"
          }
        },
        "publicationTypes": {
          "type": "array",
          "description": "The type of this publication.",
          "example": [
            "Journal Article",
            "Review"
          ],
          "items": {
            "type": "string"
          }
        },
        "publicationDate": {
          "type": "string",
          "description": "The date when this paper was published, in YYYY-MM-DD format.",
          "example": "2024-04-29"
        },
        "journal": {
          "type": "object",
          "description": "An object that contains the following parameters, if available: name (the journal name), volume (the journal\u2019s volume number), and pages (the page number range)",
          "example": {
            "volume": "40",
            "pages": "116 - 135",
            "name": "IETE Technical Review"
          }
        },
        "citationStyles": {
          "type": "object",
          "description": "The BibTex bibliographical citation of the paper.",
          "example": {
            "bibtex": "@['JournalArticle', 'Conference']{Ammar2018ConstructionOT,\n author = {Waleed Ammar and Dirk Groeneveld and Chandra Bhagavatula and Iz Beltagy and Miles Crawford and Doug Downey and Jason Dunkelberger and Ahmed Elgohary and Sergey Feldman and Vu A. Ha and Rodney Michael Kinney and Sebastian Kohlmeier and Kyle Lo and Tyler C. Murray and Hsu-Han Ooi and Matthew E. Peters and Joanna L. Power and Sam Skjonsberg and Lucy Lu Wang and Christopher Wilhelm and Zheng Yuan and Madeleine van Zuylen and Oren Etzioni},\n booktitle = {NAACL},\n pages = {84-91},\n title = {Construction of the Literature Graph in Semantic Scholar},\n year = {2018}\n}\n"
          }
        },
        "authors": {
          "type": "array",
          "items": {
            "title": "Author Info",
            "allOf": [
              {
                "$ref": "#/definitions/AuthorInPaper"
              }
            ]
          }
        },
        "citations": {
          "type": "array",
          "title": "Paper Info",
          "items": {
            "$ref": "#/definitions/BasePaper"
          }
        },
        "references": {
          "type": "array",
          "items": {
            "title": "Paper Info",
            "allOf": [
              {
                "$ref": "#/definitions/BasePaper"
              }
            ]
          }
        },
        "embedding": {
          "$ref": "#/definitions/Embedding"
        },
        "tldr": {
          "$ref": "#/definitions/Tldr"
        },
        "textAvailability": {
          "type": "string",
          "description": "fulltext, abstract, or none, based on what we have available for this paper"
        }
      },
      "type": "object"
    },
    "AuthorInPaper": {
      "properties": {
        "authorId": {
          "type": "string",
          "title": "This field will be provided if no fields are specified",
          "description": "Semantic Scholar\u2019s unique ID for the author.",
          "example": "1741101"
        },
        "externalIds": {
          "type": "object",
          "description": "An object that contains the ORCID/DBLP IDs for the author, if known.",
          "example": {
            "DBLP": [
              123
            ]
          }
        },
        "url": {
          "type": "string",
          "description": "URL of the author on the Semantic Scholar website.",
          "example": "https://www.semanticscholar.org/author/1741101"
        },
        "name": {
          "type": "string",
          "title": "This field will be provided if no fields are specified",
          "description": "Author\u2019s name.",
          "example": "Oren Etzioni"
        },
        "affiliations": {
          "type": "array",
          "description": "Array of organizational affiliations for the author.",
          "example": [
            "Allen Institute for AI"
          ],
          "items": {
            "type": "string"
          }
        },
        "homepage": {
          "type": "string",
          "description": "The author\u2019s homepage.",
          "example": "https://allenai.org/"
        },
        "paperCount": {
          "type": "string",
          "description": "The author's total publications count.",
          "example": 10
        },
        "citationCount": {
          "type": "string",
          "description": "The author's total citations count.",
          "example": 50
        },
        "hIndex": {
          "type": "string",
          "description": "The author\u2019s h-index, which is a measure of the productivity and citation impact of the author\u2019s publications: https://www.semanticscholar.org/faq#h-index",
          "example": 5
        },
        "normalizedAffiliations": {
          "type": "array",
          "description": "Array of organizational ROR-based normalized affiliations for the author (ROR - Research Organization Registry).",
          "example": [
            {
              "rorId": "https://ror.org/05w520734",
              "rorDisplayName": "Allen Institute for Artificial Intelligence"
            }
          ],
          "items": {
            "$ref": "#/definitions/NormalizedAffiliation"
          }
        }
      },
      "type": "object"
    },
    "NormalizedAffiliation": {
      "properties": {
        "rorId": {
          "type": "string",
          "description": "ROR (Research Organization Registry) unique ID.",
          "example": "https://ror.org/05w520734"
        },
        "rorDisplayName": {
          "type": "string",
          "description": "Official ROR display name.",
          "example": "Allen Institute for Artificial Intelligence"
        }
      },
      "type": "object"
    },
    "BasePaper": {
      "properties": {
        "paperId": {
          "type": "string",
          "description": "Semantic Scholar\u2019s primary unique identifier for a paper.",
          "example": "5c5751d45e298cea054f32b392c12c61027d2fe7"
        },
        "corpusId": {
          "type": "integer",
          "description": "Semantic Scholar\u2019s secondary unique identifier for a paper.",
          "example": 215416146
        },
        "externalIds": {
          "type": "object",
          "description": "An object that contains the paper\u2019s unique identifiers in external sources. The external sources are limited to: ArXiv, MAG, ACL, PubMed, Medline, PubMedCentral, DBLP, and DOI.",
          "example": {
            "MAG": "3015453090",
            "DBLP": "conf/acl/LoWNKW20",
            "ACL": "2020.acl-main.447",
            "DOI": "10.18653/V1/2020.ACL-MAIN.447",
            "CorpusId": 215416146
          }
        },
        "url": {
          "type": "string",
          "description": "URL of the paper on the Semantic Scholar website.",
          "example": "https://www.semanticscholar.org/paper/5c5751d45e298cea054f32b392c12c61027d2fe7"
        },
        "title": {
          "type": "string",
          "description": "Title of the paper.",
          "example": "Construction of the Literature Graph in Semantic Scholar"
        },
        "abstract": {
          "type": "string",
          "description": "The paper's abstract. Note that due to legal reasons, this may be missing even if we display an abstract on the website.",
          "example": "We describe a deployed scalable system for organizing published scientific literature into a heterogeneous graph to facilitate algorithmic manipulation and discovery."
        },
        "venue": {
          "type": "string",
          "description": "The name of the paper\u2019s publication venue.",
          "example": "Annual Meeting of the Association for Computational Linguistics"
        },
        "publicationVenue": {
          "type": "object",
          "description": "An object that contains the following information about the journal or conference in which this paper was published: id (the venue\u2019s unique ID), name (the venue\u2019s name), type (the type of venue), alternate_names (an array of alternate names for the venue), and url (the venue\u2019s website).",
          "example": {
            "id": "1e33b3be-b2ab-46e9-96e8-d4eb4bad6e44",
            "name": "Annual Meeting of the Association for Computational Linguistics",
            "type": "conference",
            "alternate_names": [
              "Annu Meet Assoc Comput Linguistics",
              "Meeting of the Association for Computational Linguistics",
              "ACL",
              "Meet Assoc Comput Linguistics"
            ],
            "url": "https://www.aclweb.org/anthology/venues/acl/"
          }
        },
        "year": {
          "type": "integer",
          "description": "The year the paper was published.",
          "example": 1997
        },
        "referenceCount": {
          "type": "integer",
          "description": "The total number of papers this paper references.",
          "example": 59
        },
        "citationCount": {
          "type": "integer",
          "description": "The total number of papers that references this paper.",
          "example": 453
        },
        "influentialCitationCount": {
          "type": "integer",
          "description": "A subset of the citation count, where the cited publication has a significant impact on the citing publication. Determined by Semantic Scholar\u2019s algorithm: https://www.semanticscholar.org/faq#influential-citations.",
          "example": 90
        },
        "isOpenAccess": {
          "type": "boolean",
          "description": "Whether the paper is open access. More information here: https://www.openaccess.nl/en/what-is-open-access.",
          "example": true
        },
        "openAccessPdf": {
          "type": "object",
          "description": "An object that contains the following parameters: url (a link to the paper\u2019s PDF), status (the type of open access https://en.wikipedia.org/wiki/Open_access#Colour_naming_system), the paper's license, and a legal disclaimer.",
          "example": {
            "url": "https://www.aclweb.org/anthology/2020.acl-main.447.pdf",
            "status": "HYBRID",
            "license": "CCBY",
            "disclaimer": "Notice: This snippet is extracted from the open access paper or abstract available at https://aclanthology.org/2020.acl-main.447, which is subject to the license by the author or copyright owner provided with this content. Please go to the source to verify the license and copyright information for your use."
          }
        },
        "fieldsOfStudy": {
          "type": "array",
          "description": "A list of the paper\u2019s high-level academic categories from external sources. The possible fields are: Computer Science, Medicine, Chemistry, Biology, Materials Science, Physics, Geology, Psychology, Art, History, Geography, Sociology, Business, Political Science, Economics, Philosophy, Mathematics, Engineering, Environmental Science, Agricultural and Food Sciences, Education, Law, and Linguistics.",
          "example": [
            "Computer Science"
          ],
          "items": {
            "type": "string"
          }
        },
        "s2FieldsOfStudy": {
          "type": "array",
          "description": "An array of objects. Each object contains the following parameters: category (a field of study. The possible fields are the same as in fieldsOfStudy), and source (specifies whether the category was classified by Semantic Scholar or by an external source. More information on how Semantic Scholar classifies papers https://medium.com/ai2-blog/announcing-s2fos-an-open-source-academic-field-of-study-classifier-9d2f641949e5)",
          "example": [
            {
              "category": "Computer Science",
              "source": "external"
            },
            {
              "category": "Computer Science",
              "source": "s2-fos-model"
            },
            {
              "category": "Mathematics",
              "source": "s2-fos-model"
            }
          ],
          "items": {
            "type": "object"
          }
        },
        "publicationTypes": {
          "type": "array",
          "description": "The type of this publication.",
          "example": [
            "Journal Article",
            "Review"
          ],
          "items": {
            "type": "string"
          }
        },
        "publicationDate": {
          "type": "string",
          "description": "The date when this paper was published, in YYYY-MM-DD format.",
          "example": "2024-04-29"
        },
        "journal": {
          "type": "object",
          "description": "An object that contains the following parameters, if available: name (the journal name), volume (the journal\u2019s volume number), and pages (the page number range)",
          "example": {
            "volume": "40",
            "pages": "116 - 135",
            "name": "IETE Technical Review"
          }
        },
        "citationStyles": {
          "type": "object",
          "description": "The BibTex bibliographical citation of the paper.",
          "example": {
            "bibtex": "@['JournalArticle', 'Conference']{Ammar2018ConstructionOT,\n author = {Waleed Ammar and Dirk Groeneveld and Chandra Bhagavatula and Iz Beltagy and Miles Crawford and Doug Downey and Jason Dunkelberger and Ahmed Elgohary and Sergey Feldman and Vu A. Ha and Rodney Michael Kinney and Sebastian Kohlmeier and Kyle Lo and Tyler C. Murray and Hsu-Han Ooi and Matthew E. Peters and Joanna L. Power and Sam Skjonsberg and Lucy Lu Wang and Christopher Wilhelm and Zheng Yuan and Madeleine van Zuylen and Oren Etzioni},\n booktitle = {NAACL},\n pages = {84-91},\n title = {Construction of the Literature Graph in Semantic Scholar},\n year = {2018}\n}\n"
          }
        },
        "authors": {
          "type": "array",
          "title": "Author Info",
          "description": "Details about the paper's authors",
          "items": {
            "$ref": "#/definitions/AuthorInfo"
          }
        }
      },
      "type": "object"
    },
    "AuthorInfo": {
      "properties": {
        "authorId": {
          "type": "string",
          "title": "This field will be provided if no fields are specified",
          "description": "Semantic Scholar\u2019s unique ID for the author.",
          "example": "1741101"
        },
        "name": {
          "type": "string",
          "title": "This field will be provided if no fields are specified",
          "description": "Author\u2019s name.",
          "example": "Oren Etzioni"
        }
      },
      "type": "object"
    },
    "Embedding": {
      "properties": {
        "model": {
          "type": "string",
          "description": "The Spector vector embedding model version: https://github.com/allenai/specter",
          "example": "[email protected]"
        },
        "vector": {
          "type": "object",
          "description": "Numerical embedding vector.",
          "example": [
            -8.82082748413086,
            -2.6610865592956543
          ]
        }
      },
      "type": "object"
    },
    "Tldr": {
      "properties": {
        "model": {
          "type": "string",
          "description": "The tldr model version number: https://github.com/allenai/scitldr",
          "example": "[email protected]"
        },
        "text": {
          "type": "string",
          "description": "The tldr paper summary.",
          "example": "This paper reduces literature graph construction into familiar NLP tasks, point out research challenges due to differences from standard formulations of these tasks, and report empirical results for each task."
        }
      },
      "type": "object"
    },
    "PaperBatch": {
      "properties": {
        "ids": {
          "type": "array",
          "items": {
            "type": "string",
            "example": "649def34f8be52c8b66281af98ae884c09aef38b"
          }
        }
      },
      "type": "object"
    },
    "CitationBatch": {
      "properties": {
        "offset": {
          "type": "integer",
          "description": "Starting position for this batch."
        },
        "next": {
          "type": "integer",
          "description": "Starting position of the next batch. Absent if no more data exists."
        },
        "data": {
          "type": "array",
          "items": {
            "title": "contents of this batch",
            "allOf": [
              {
                "$ref": "#/definitions/Citation"
              }
            ]
          }
        }
      },
      "type": "object"
    },
    "Citation": {
      "properties": {
        "contexts": {
          "type": "array",
          "description": "Array of text snippets where the reference to the paper is mentioned.",
          "example": [
            "SciBERT (Beltagy et al., 2019) follows the BERT\u2019s masking strategy to pre-train the model from scratch using a scientific corpus composed of papers from Semantic Scholar (Ammar et al., 2018).",
            "27M articles from the Semantic Scholar dataset (Ammar et al., 2018)."
          ],
          "items": {
            "type": "string"
          }
        },
        "intents": {
          "type": "array",
          "description": "Array of citation intents that summarizes how the reference to the paper is mentioned. Possible intents: https://www.semanticscholar.org/faq#citation-intent",
          "example": [
            "methodology"
          ],
          "items": {
            "type": "string"
          }
        },
        "contextsWithIntent": {
          "type": "array",
          "description": "Array of objects that contain both contexts and the intents they are associated with.",
          "example": [
            {
              "context": "SciBERT (Beltagy et al., 2019) follows the BERT\u2019s ...",
              "intents": [
                "methodology"
              ]
            }
          ],
          "items": {
            "type": "object"
          }
        },
        "isInfluential": {
          "type": "boolean",
          "description": "Whether the citing paper is highly influential. See more about influential citations: https://www.semanticscholar.org/faq#influential-citations",
          "example": false
        },
        "citingPaper": {
          "description": "Details about the citing paper",
          "allOf": [
            {
              "$ref": "#/definitions/BasePaper"
            }
          ]
        }
      },
      "type": "object"
    },
    "ReferenceBatch": {
      "properties": {
        "offset": {
          "type": "integer",
          "description": "Starting position for this batch."
        },
        "next": {
          "type": "integer",
          "description": "Starting position of the next batch. Absent if no more data exists."
        },
        "data": {
          "type": "array",
          "items": {
            "title": "contents of this batch",
            "allOf": [
              {
                "$ref": "#/definitions/Reference"
              }
            ]
          }
        }
      },
      "type": "object"
    },
    "Reference": {
      "properties": {
        "contexts": {
          "type": "array",
          "description": "Array of text snippets where the reference to the paper is mentioned.",
          "example": [
            "SciBERT (Beltagy et al., 2019) follows the BERT\u2019s masking strategy to pre-train the model from scratch using a scientific corpus composed of papers from Semantic Scholar (Ammar et al., 2018).",
            "27M articles from the Semantic Scholar dataset (Ammar et al., 2018)."
          ],
          "items": {
            "type": "string"
          }
        },
        "intents": {
          "type": "array",
          "description": "Array of citation intents that summarizes how the reference to the paper is mentioned. Possible intents: https://www.semanticscholar.org/faq#citation-intent",
          "example": [
            "methodology"
          ],
          "items": {
            "type": "string"
          }
        },
        "contextsWithIntent": {
          "type": "array",
          "description": "Array of objects that contain both contexts and the intents they are associated with.",
          "example": [
            {
              "context": "SciBERT (Beltagy et al., 2019) follows the BERT\u2019s ...",
              "intents": [
                "methodology"
              ]
            }
          ],
          "items": {
            "type": "object"
          }
        },
        "isInfluential": {
          "type": "boolean",
          "description": "Whether the citing paper is highly influential. See more about influential citations: https://www.semanticscholar.org/faq#influential-citations",
          "example": false
        },
        "citedPaper": {
          "description": "Details about the cited paper",
          "allOf": [
            {
              "$ref": "#/definitions/BasePaper"
            }
          ]
        }
      },
      "type": "object"
    },
    "AuthorBatch": {
      "properties": {
        "offset": {
          "type": "integer",
          "description": "Starting position for this batch."
        },
        "next": {
          "type": "integer",
          "description": "Starting position of the next batch. Absent if no more data exists."
        },
        "data": {
          "type": "array",
          "items": {
            "title": "contents of this batch",
            "allOf": [
              {
                "$ref": "#/definitions/AuthorInPaperWithPapers"
              }
            ]
          }
        }
      },
      "type": "object"
    },
    "AuthorInPaperWithPapers": {
      "properties": {
        "authorId": {
          "type": "string",
          "title": "This field will be provided if no fields are specified",
          "description": "Semantic Scholar\u2019s unique ID for the author.",
          "example": "1741101"
        },
        "externalIds": {
          "type": "object",
          "description": "An object that contains the ORCID/DBLP IDs for the author, if known.",
          "example": {
            "DBLP": [
              123
            ]
          }
        },
        "url": {
          "type": "string",
          "description": "URL of the author on the Semantic Scholar website.",
          "example": "https://www.semanticscholar.org/author/1741101"
        },
        "name": {
          "type": "string",
          "title": "This field will be provided if no fields are specified",
          "description": "Author\u2019s name.",
          "example": "Oren Etzioni"
        },
        "affiliations": {
          "type": "array",
          "description": "Array of organizational affiliations for the author.",
          

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