Triple

T2852740
Position Surface form Disambiguated ID Type / Status
Subject Hudson Line E63128 entity
Predicate regionServed P82 FINISHED
Object Putnam County E15885 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: Putnam County | Statement: [Hudson Line, regionServed, Putnam County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Putnam County
Context triple: [Hudson Line, regionServed, Putnam County]
  • A. Putnam County chosen
    Putnam County is a suburban county in southeastern New York State known for its lakes, forests, and commuter communities north of New York City.
  • B. Dickinson County
    Dickinson County is a county in central Kansas known for including the city of Abilene, a historic cattle town and the boyhood home of President Dwight D. Eisenhower.
  • C. Clinton County
    Clinton County is the name of numerous counties in the United States, typically named after prominent American statesmen such as George Clinton or DeWitt Clinton.
  • D. Monroe County
    Monroe County is a county in central Georgia known for its mix of rural communities, historic towns like Forsyth, and its location along major transportation routes between Atlanta and Macon.
  • E. Monroe County
    Monroe County is a rural county in southern West Virginia known for its scenic Appalachian landscapes, agriculture, and historic small towns.
  • 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_69ab4c407c408190857d25e027155ce9 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdf5e043c8190ac82112abce7262a completed March 7, 2026, 8:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69b555ff48c48190865f0d588ec5d296 completed March 14, 2026, 12:35 p.m.
Created at: March 6, 2026, 10:02 p.m.