Triple

T2667165
Position Surface form Disambiguated ID Type / Status
Subject Elias Loomis E55662 entity
Predicate workLocation P7 FINISHED
Object Hudson, Ohio E252444 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: Hudson, Ohio | Statement: [Elias Loomis, workLocation, Hudson, Ohio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hudson, Ohio
Context triple: [Elias Loomis, workLocation, Hudson, Ohio]
  • A. Hudson, Ohio chosen
    Hudson, Ohio is a small city in northeastern Ohio known for its historic New England–style downtown and as a center of education and culture in the region.
  • B. Huron, Ohio
    Huron, Ohio is a small city on the southern shore of Lake Erie known for its waterfront, marinas, and proximity to regional attractions like Cedar Point.
  • C. Thurston, Ohio
    Thurston, Ohio is a small village located in Fairfield County in the central part of the state.
  • D. Wakeman, Ohio
    Wakeman, Ohio is a small village in northern Ohio known for its rural character and location within Huron County.
  • E. Havana, Ohio
    Havana, Ohio is a small unincorporated community located in Huron County in north-central Ohio.
  • 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_69ab49e54de48190be708cd1cf8be073 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd97040e48190b0a87489f108810e completed March 7, 2026, 7:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69b5f57163e08190934045ea34486605 completed March 14, 2026, 11:55 p.m.
Created at: March 6, 2026, 9:54 p.m.