Triple

T122024
Position Surface form Disambiguated ID Type / Status
Subject MAX Red Line E2466 entity
Predicate regionServed P82 FINISHED
Object Washington County E20228 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: Washington County | Statement: [MAX Red Line, regionServed, Washington County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Washington County
Context triple: [MAX Red Line, regionServed, Washington County]
  • A. Washington County chosen
    Washington County is a county in southwestern Pennsylvania that forms part of the greater Pittsburgh metropolitan area.
  • B. Washington County
    Washington County was a former administrative subdivision of the District of Columbia that encompassed the area outside the cities of Washington and Georgetown on the Maryland side of the Potomac River.
  • C. Pike County
    Pike County is a county in west-central Georgia, United States, known for its rural character and location within the Atlanta metropolitan area’s broader region.
  • D. 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.
  • E. Butler County
    Butler County is a county in western Pennsylvania, north of Pittsburgh, known for its mix of suburban communities, rural landscapes, and growing industrial and service sectors.
  • 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_69a2506c5428819085c28a8884790e29 completed Feb. 28, 2026, 2:18 a.m.
NER Named-entity recognition batch_69a25739ef28819093f3f0e6bb670201 completed Feb. 28, 2026, 2:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69a31619063c8190879a726867d4b46d completed Feb. 28, 2026, 4:21 p.m.
Created at: Feb. 28, 2026, 2:24 a.m.