Triple

T5384672
Position Surface form Disambiguated ID Type / Status
Subject Waterloo station E113173 entity
Predicate railcode P27071 FINISHED
Object WAT E250114 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: WAT | Statement: [Waterloo station, railcode, WAT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: WAT
Context triple: [Waterloo station, railcode, WAT]
  • A. WAT chosen
    WAT is the National Rail station code for London Waterloo, one of the busiest and most important railway terminals in the United Kingdom.
  • B. Wat
    Wat is a medieval English diminutive form of the given name Walter, historically used as a familiar or nickname.
  • C. WAW
    WAW is the three-letter IATA airport code for Warsaw Chopin Airport, the primary international airport serving Warsaw, Poland.
  • D. WAS
    WAS is the standard three-letter abbreviation used for the Washington Commanders NFL franchise.
  • E. WAS
    WAS is the standard three-letter abbreviation used for the NBA team Washington Wizards.
  • 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_69bd4436a1988190af18dcff7fd306b4 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd86f5a7388190aa4ba2052afca74e completed March 20, 2026, 5:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf295030b081909bea5e946aac098b completed March 21, 2026, 11:27 p.m.
Created at: March 20, 2026, 2:03 p.m.