Triple

T2548037
Position Surface form Disambiguated ID Type / Status
Subject Capability Brown E57951 entity
Predicate nickname P55 FINISHED
Object Capability Brown E57951 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: Capability Brown | Statement: [Capability Brown, nickname, Capability Brown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Capability Brown
Context triple: [Capability Brown, nickname, Capability Brown]
  • A. Capability Brown chosen
    Capability Brown was an 18th-century English landscape architect renowned for transforming grand country estates into naturalistic, sweeping parklands that defined the English landscape garden style.
  • B. Mark Brown
    Mark Brown is an American filmmaker and screenwriter best known for writing and directing the romantic comedy film "Two Can Play That Game."
  • C. Jonathan Brown
    Jonathan Brown is a cinematographer best known for his work on major studio comedies and mainstream Hollywood films, including the 2006 reboot of The Pink Panther.
  • D. Christopher Browne
    Christopher Browne is a screenwriter known for his work on the biographical drama film "The Walk."
  • E. John Grandy
    John Grandy was a senior Royal Air Force officer who rose to become a leading commander of British fighter forces during and after the Second World War.
  • 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_69ab4a5212d88190b989ce129f2ad87f completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd2e672948190bb7fe9b47535a172 completed March 7, 2026, 7:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69af5d0e6e188190be190965cc02838e completed March 9, 2026, 11:51 p.m.
Created at: March 6, 2026, 9:47 p.m.