Triple

T14576056
Position Surface form Disambiguated ID Type / Status
Subject Nick Harvey E342052 entity
Predicate workLocation P7 FINISHED
Object Westminster E14557 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 | Statement: [Nick Harvey, workLocation, Westminster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Westminster
Context triple: [Nick Harvey, workLocation, Westminster]
  • A. 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.
  • B. Westminster
    Westminster is a city in Orange County, California, known for its large Vietnamese-American community and vibrant Little Saigon district.
  • C. 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.
  • D. Westminster
    Westminster is a small New England town in northern Massachusetts known for its rural character, historic charm, and proximity to the Wachusett Mountain area.
  • E. City of Westminster chosen
    The City of Westminster is a central London borough that serves as the political and ceremonial heart of the United Kingdom, encompassing landmarks such as the Houses of Parliament, Buckingham Palace, and major government institutions.
  • 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_69d822dcc6248190bed689984bceb0e2 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb3f5ec448190b2ef887fdf7b633e completed April 14, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd8ab414dc8190a233185068cfb8ff completed May 8, 2026, 7:03 a.m.
Created at: April 10, 2026, 1:24 a.m.