Triple

T22204121
Position Surface form Disambiguated ID Type / Status
Subject Durham Women E548758 entity
Predicate participatesIn P149 FINISHED
Object FA Women's Cup 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: FA Women's Cup | Statement: [Durham Women, participatesIn, FA Women's Cup]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: FA Women's Cup
Context triple: [Durham Women, participatesIn, FA Women's Cup]
  • A. FA Women's Cup chosen
    The FA Women's Cup is England's premier national knockout cup competition in women's football, organized by The Football Association.
  • B. FA Women's Championship
    The FA Women's Championship is the second-highest division in the English women's football league system, sitting below the Women's Super League.
  • C. FAW Women's Cup
    The FAW Women's Cup is the premier national women's football knockout competition in Wales, featuring clubs from across the Welsh football pyramid.
  • D. Nadeshiko League
    The Nadeshiko League is Japan’s premier women’s football league, featuring the country’s top female clubs and players.
  • E. All Japan Women's Football Championship
    The All Japan Women's Football Championship is a premier national knockout tournament that determines Japan's top women's football club each year.
  • 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_69e11e3ecc7c8190b5f94cd8f42e9d37 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12b25eac4819094b3c50027ed66db completed April 28, 2026, 9:48 p.m.
Created at: April 16, 2026, 8:36 p.m.