Triple

T738153
Position Surface form Disambiguated ID Type / Status
Subject Econometrica E14979 entity
Predicate indexedIn P1393 FINISHED
Object Scopus E16219 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Scopus | Statement: [Econometrica, indexedIn, Scopus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Scopus
Context triple: [Econometrica, indexedIn, Scopus]
  • A. Scopus chosen
    Scopus is a large abstract and citation database of peer-reviewed literature covering scientific, technical, medical, and social science research.
  • B. Web of Science
    Web of Science is a major multidisciplinary citation indexing and abstracting database widely used for academic research and bibliometric analysis.
  • C. Ei Compendex
    Ei Compendex is a comprehensive engineering literature database that indexes scientific and technical research publications across a wide range of engineering disciplines.
  • D. Clarivate Analytics
    Clarivate Analytics is a global analytics company specializing in providing research, citation, patent, and intellectual property data and tools for academia, corporations, and governments.
  • E. Science Citation Index
    The Science Citation Index is a multidisciplinary citation database that tracks and indexes scientific journal articles to measure research impact and facilitate literature discovery.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a4934d9930819099eed80096b0597d completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a5f1c9888190b2817138c6893cfe completed March 1, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69a76d742ef08190bb9405a1cde84eb1 completed March 3, 2026, 11:23 p.m.
Created at: March 1, 2026, 7:37 p.m.