Triple

T15888644
Position Surface form Disambiguated ID Type / Status
Subject Nottingham Forest Football Club area E385257 entity
Predicate hasPart P35 FINISHED
Object City Ground E549811 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: City Ground | Statement: [Nottingham Forest Football Club area, hasPart, City Ground]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City Ground
Context triple: [Nottingham Forest Football Club area, hasPart, City Ground]
  • A. City Ground chosen
    City Ground is a football stadium in Nottingham, England, best known as the long-time home of Nottingham Forest F.C.
  • B. Castlefield
    Castlefield is a historic urban area in Manchester, England, known for its preserved industrial heritage, canals, and Roman origins.
  • C. London Fields
    London Fields is a popular public park in the London Borough of Hackney known for its open green space, lido, and vibrant community atmosphere.
  • D. Castlefields
    Castlefields is a residential suburb within the town of Runcorn in Cheshire, England.
  • E. Everedy Square
    Everedy Square is a historic shopping and dining complex in downtown Frederick, Maryland, known for its restored industrial buildings, boutiques, and local restaurants.
  • 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_69d86da5b800819083a31be937d738b0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1561c3d008190a892f091a2f874cf completed April 16, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb04598e0819094274868941195b9 completed May 9, 2026, 10:08 p.m.
Created at: April 10, 2026, 4:51 a.m.