Triple

T12017185
Position Surface form Disambiguated ID Type / Status
Subject Denis Compton E286056 entity
Predicate placeOfDeath P21 FINISHED
Object Windsor E34732 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: Windsor | Statement: [Denis Compton, placeOfDeath, Windsor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Windsor
Context triple: [Denis Compton, placeOfDeath, Windsor]
  • A. Windsor chosen
    Windsor is a historic English town in Berkshire best known for Windsor Castle, one of the official residences of the British monarch and a major royal and military ceremonial site.
  • B. Windsor
    Windsor is a Canadian city in southwestern Ontario located directly across the Detroit River from Detroit, known for its automotive industry and role as a key border crossing between Canada and the United States.
  • C. Windsor
    Windsor is a village in south-central Wisconsin, United States, located just north of the city of Madison.
  • D. Windsor
    Windsor is a small town in northern Colorado known for its rapidly growing residential communities and proximity to major Front Range cities like Fort Collins and Greeley.
  • E. Windsor
    Windsor is a historic town in Connecticut recognized as the state's first English settlement and now part of the Hartford metropolitan area.
  • 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_69d6ab45a368819084fce08bf0dc3705 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903d9b17881908894be80d7c1b64e completed April 10, 2026, 2:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f64464a48190a2b96e39ab411115 completed May 2, 2026, 1:04 p.m.
Created at: April 8, 2026, 9:47 p.m.