Triple

T2279401
Position Surface form Disambiguated ID Type / Status
Subject Woodsworth College E51246 entity
Predicate hasAbbreviation P43 FINISHED
Object WW E51246 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: WW | Statement: [Woodsworth College, hasAbbreviation, WW]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: WW
Context triple: [Woodsworth College, hasAbbreviation, WW]
  • A. WW chosen
    WW is the commonly used abbreviation for Woodsworth College, a constituent college of the University of Toronto known for its diverse student body and focus on continuing and part-time education.
  • B. W
    The W is a local New York City Subway service that runs on the BMT Broadway Line in Manhattan and Queens, typically operating on weekdays.
  • C. W
    W is one of the iconic white capital letters that make up the famous Hollywood Sign overlooking Los Angeles.
  • D. WN
    WN is the IATA airline designator used to identify Southwest Airlines in flight schedules, ticketing, and aviation operations.
  • E. WR
    WR is the abbreviation for the German Council of Science and Humanities, a key advisory body that counsels the German federal and state governments on science, research, and higher education policy.
  • 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_69a88b08e4308190bdac9aebcca1c91a completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abc2194150819083156e4dcd45a423 completed March 7, 2026, 6:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae71e48fb081908498f826167020a2 completed March 9, 2026, 7:08 a.m.
Created at: March 4, 2026, 7:48 p.m.