Triple

T12214772
Position Surface form Disambiguated ID Type / Status
Subject Davis Mountains E291052 entity
Predicate administrativeRegion P285 FINISHED
Object Jeff Davis County E899910 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: Jeff Davis County | Statement: [Davis Mountains, administrativeRegion, Jeff Davis County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jeff Davis County
Context triple: [Davis Mountains, administrativeRegion, Jeff Davis County]
  • A. Jeff Davis County
    Jeff Davis County is a rural county in southeastern Georgia known for its small-town communities and agricultural landscape.
  • B. Jeff Davis County chosen
    Jeff Davis County is a sparsely populated county in West Texas known for its mountainous terrain, dark skies, and the town of Fort Davis.
  • C. Van Zandt County
    Van Zandt County is a rural county in northeastern Texas known for its agricultural heritage and small-town communities.
  • D. Cottle County
    Cottle County is a sparsely populated rural county in north-central Texas known for its ranching, agriculture, and small-town communities.
  • E. Haskell County
    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.
  • 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_69d6ab65923081909acfc61b7a612233 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91c931cec819083ca19be06a33e1c completed April 10, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68e9fc934819089f68bcc823015da completed May 2, 2026, 11:54 p.m.
Created at: April 8, 2026, 9:51 p.m.