Triple

T6675585
Position Surface form Disambiguated ID Type / Status
Subject Warren County, New York E151842 entity
Predicate contains P35 FINISHED
Object Town of Warrensburg E368384 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: Town of Warrensburg | Statement: [Warren County, New York, contains, Town of Warrensburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Town of Warrensburg
Context triple: [Warren County, New York, contains, Town of Warrensburg]
  • A. Warrensburg, New York chosen
    Warrensburg, New York is a small town in Warren County in the Adirondack region, known as a local commercial center and gateway to nearby outdoor recreation areas.
  • B. Town of Ward
    The Town of Ward is a small rural municipality located in Allegany County in western New York State.
  • C. Village of Warren
    The Village of Warren was an earlier municipal incarnation of what later became the city of Warren, Michigan.
  • D. Town of Nunda
    The Town of Nunda is a small rural municipality in western New York State known for its agricultural landscape and proximity to the Genesee River Valley.
  • E. Town of Wirt
    The Town of Wirt is a small rural municipality in Allegany County in western New York State, known for its quiet countryside and low population density.
  • 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_69c687f830bc81909eb8b04dbb8450b1 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b0f3021481908c2599349eb6ea07 completed March 27, 2026, 4:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6f7a30b7481908c36ff9035f62731 completed March 27, 2026, 9:33 p.m.
Created at: March 27, 2026, 2:03 p.m.