Triple

T15940220
Position Surface form Disambiguated ID Type / Status
Subject Reeves County E386537 entity
Predicate borderedBy P224 FINISHED
Object Loving County E253851 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: Loving County | Statement: [Reeves County, borderedBy, Loving County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Loving County
Context triple: [Reeves County, borderedBy, Loving County]
  • A. Loving County chosen
    Loving County is a sparsely populated county in western Texas known for being one of the least populous counties in the United States.
  • B. Plumas County
    Plumas County is a rural, mountainous county in northeastern California known for its forests, lakes, and outdoor recreation within the northern Sierra Nevada.
  • C. Eddy County
    Eddy County is a county in southeastern New Mexico known for encompassing Carlsbad Caverns National Park and significant oil and gas production.
  • D. Carson County
    Carson County is a rural county in the Texas Panhandle known for its agricultural economy and small-town communities.
  • E. Teller County
    Teller County is a mountainous county in central Colorado known for its historic gold mining communities, including the city of Cripple Creek.
  • 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_69d86da750008190987eb26be3f6c118 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e156cd3a188190a1a7dcbfdd38284c completed April 16, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb5ba070c8190b6af6cb21bddd7f1 completed May 9, 2026, 10:31 p.m.
Created at: April 10, 2026, 4:53 a.m.