Triple

T12966920
Position Surface form Disambiguated ID Type / Status
Subject Muskogee County E321284 entity
Predicate hasBorderWith P224 FINISHED
Object Haskell County E756057 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: Haskell County | Statement: [Muskogee County, hasBorderWith, Haskell County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haskell County
Context triple: [Muskogee County, hasBorderWith, Haskell County]
  • A. Haskell County chosen
    Haskell County is a rural county in eastern Oklahoma, United States, known for its small communities and location within the region commonly referred to as Green Country.
  • B. Cottle County
    Cottle County is a sparsely populated rural county in north-central Texas known for its ranching, agriculture, and small-town communities.
  • C. Reagan County
    Reagan County is a sparsely populated county in West Texas known for its oil and gas production and its county seat, Big Lake.
  • D. Logan County
    Logan County is a largely rural, coal-mining region in southern West Virginia known for its Appalachian landscape and history.
  • E. Logan County
    Logan County is a largely rural county in northeastern Colorado known for its agricultural economy and small communities such as its county seat, Sterling.
  • 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_69d80763bd6c819094437da5b20b01d2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e3f702481908f0f90f4f12d3f4d completed April 10, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f716b885708190b6c38c481fa9ca21 completed May 3, 2026, 9:34 a.m.
Created at: April 9, 2026, 8:30 p.m.