Triple

T16748769
Position Surface form Disambiguated ID Type / Status
Subject Microsoft Academic Search E407020 entity
Predicate competitor P1375 FINISHED
Object Google Scholar E91284 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: Google Scholar | Statement: [Microsoft Academic Search, competitor, Google Scholar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Google Scholar
Context triple: [Microsoft Academic Search, competitor, Google Scholar]
  • A. Google Scholar chosen
    Google Scholar is a freely accessible academic search engine that indexes scholarly literature across many disciplines and formats, helping researchers find articles, theses, books, conference papers, and more.
  • B. Semantic Scholar
    Semantic Scholar is an AI-powered academic search engine that helps researchers discover and understand scientific literature more efficiently.
  • C. CiteSeerX
    CiteSeerX is a public digital library and search engine that focuses on indexing and providing access to scientific and academic research papers, particularly in computer and information science.
  • D. Scopus
    Scopus is a large abstract and citation database of peer-reviewed literature covering scientific, technical, medical, and social science research.
  • E. DBLP
    DBLP is a comprehensive computer science bibliography database that indexes research papers, conference proceedings, and journals in the field of computing.
  • 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_69d8838ffb088190a0b11149929006bf completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3aa2532ac81908e5ee5148e35f92e completed April 18, 2026, 3:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00a522255c8190ab16d7ad233fcd3b completed May 10, 2026, 3:32 p.m.
Created at: April 10, 2026, 5:21 a.m.