Triple

T17618304
Position Surface form Disambiguated ID Type / Status
Subject Psychological Review E429141 entity
Predicate indexingService P6000 FINISHED
Object Scopus NE NERFINISHED

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: [Psychological Review, indexingService, Scopus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Scopus
Context triple: [Psychological Review, indexingService, 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. SCImago Research Group
    SCImago Research Group is an academic research organization best known for creating bibliometric indicators and journal rankings that analyze and visualize scientific output and impact worldwide.
  • E. SciVal
    SciVal is an Elsevier analytics platform that provides research performance metrics and benchmarking tools for institutions, researchers, and policymakers.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889e1c6148190ba76241e74688f8b completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46d3489dc8190a619c58025dbb250 completed April 19, 2026, 5:50 a.m.
Created at: April 10, 2026, 5:51 a.m.