Triple

T6845083
Position Surface form Disambiguated ID Type / Status
Subject Esther Cleveland E157873 entity
Predicate placeOfMarriage P128 FINISHED
Object Westminster, London E77156 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: Westminster, London | Statement: [Esther Cleveland, placeOfMarriage, Westminster, London]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Westminster, London
Context triple: [Esther Cleveland, placeOfMarriage, Westminster, London]
  • A. Westminster
    Westminster is a city in Orange County, California, known for its large Vietnamese-American community and vibrant Little Saigon district.
  • B. Westminster
    Westminster is a city in northern Maryland that serves as the county seat of Carroll County and a regional hub for the surrounding communities.
  • C. Westminster
    Westminster is a suburban city in the Denver metropolitan area of Colorado, known for its residential communities, parks, and proximity to the Rocky Mountains.
  • D. Westminster, London, England chosen
    Westminster, London, England is a central district of the UK capital known for housing key government institutions, royal landmarks, and major historical sites.
  • E. London Victoria
    London Victoria is a major central London railway terminus and Underground station, serving as a key hub for commuter, regional, and Gatwick Airport services.
  • 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_69c6882ed4c081909dc465a7cf8838be completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d6b8627081908e34d2b942d08aef completed March 27, 2026, 7:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69c748b5a7c08190983bd355a1bc76d7 completed March 28, 2026, 3:19 a.m.
Created at: March 27, 2026, 2:19 p.m.