Triple

T3956989
Position Surface form Disambiguated ID Type / Status
Subject Schoharie Creek E85805 entity
Predicate flowsThrough P225 FINISHED
Object Greene County E162949 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: Greene County | Statement: [Schoharie Creek, flowsThrough, Greene County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Greene County
Context triple: [Schoharie Creek, flowsThrough, Greene County]
  • A. Greene County chosen
    Greene County is a rural county in eastern New York State known for encompassing a significant portion of the scenic Catskill Mountains.
  • B. Greene County
    Greene County is a rural county in southwestern Pennsylvania known for its Appalachian landscape, coal mining history, and small-town communities within the greater Pittsburgh region.
  • C. Greene County
    Greene County is a rural county in western Alabama known for its historical significance in the Black Belt region and its predominantly African American population.
  • D. Madison County
    Madison County is a county in central Mississippi, located in the Jackson metropolitan area and known for its rapidly growing suburban communities.
  • E. Madison County
    Madison County is a county in central New York State known for its rural communities, agriculture, and small historic towns such as Oneida and Cazenovia.
  • 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_69aed93a96908190bcbdbfa718f155bd completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef95bbb9c8190bd64c5b7ea2f341a completed March 9, 2026, 4:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69be031d16a08190b84524b7153f7f85 completed March 21, 2026, 2:31 a.m.
Created at: March 9, 2026, 3:31 p.m.