Triple

T16748873
Position Surface form Disambiguated ID Type / Status
Subject Google Scholar E407022 entity
Predicate supportsCitationFormat P108174 FINISHED
Object RefMan E407018 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: RefMan | Statement: [Google Scholar, supportsCitationFormat, RefMan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RefMan
Context triple: [Google Scholar, supportsCitationFormat, RefMan]
  • A. RefMan chosen
    RefMan is a bibliographic reference management file format used for exporting and importing citation data between academic databases and reference management software.
  • B. REFER
    REFER was Portugal’s former state-owned rail infrastructure company responsible for managing and maintaining the national railway network before its merger into Infraestruturas de Portugal.
  • C. BibDesk
    BibDesk is a macOS reference management application designed to help users organize and cite bibliographic data, especially for LaTeX documents.
  • D. RefWorks
    RefWorks is a web-based reference management tool that helps researchers collect, organize, and format citations and bibliographies in various academic styles.
  • E. FRBRoo
    FRBRoo is an object-oriented conceptual model that harmonizes the FRBR bibliographic framework with the CIDOC CRM ontology to support rich, interoperable descriptions of cultural heritage and bibliographic information.
  • 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.