Triple

T2242197
Position Surface form Disambiguated ID Type / Status
Subject Central Massachusetts E49421 entity
Predicate containsCity P294 FINISHED
Object Leominster E208192 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: Leominster | Statement: [Central Massachusetts, containsCity, Leominster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leominster
Context triple: [Central Massachusetts, containsCity, Leominster]
  • A. Leominster
    Leominster is a historic market town in Herefordshire, England, known for its medieval architecture and agricultural heritage.
  • B. Leominster, Massachusetts chosen
    Leominster, Massachusetts is a small city in north-central Massachusetts known historically for its plastics industry and as the birthplace of the modern plastic comb.
  • C. Fitchburg
    Fitchburg is a small city in north-central Massachusetts known for its industrial history, hilly terrain, and role as a regional rail hub.
  • D. Springfield, Maine
    Springfield, Maine is a small rural town located in Penobscot County in eastern Maine, known for its forested landscape and quiet, sparsely populated setting.
  • E. Thomaston, Maine
    Thomaston, Maine is a small coastal town in Knox County known for its historic architecture, shipbuilding heritage, and association with Revolutionary War general Henry Knox.
  • 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_69a88aa979788190ad6500f1d8eee2fc completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc0c017548190a71fb4a0e2a8189f completed March 7, 2026, 6:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebf1cded88190aa8edefc5dd94a6c completed March 9, 2026, 12:37 p.m.
Created at: March 4, 2026, 7:47 p.m.