Triple

T13215232
Position Surface form Disambiguated ID Type / Status
Subject Crosby County Courthouse E314594 entity
Predicate county P75 FINISHED
Object Crosby County E299524 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: Crosby County | Statement: [Crosby County Courthouse, county, Crosby County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Crosby County
Context triple: [Crosby County Courthouse, county, Crosby County]
  • A. Crosby County chosen
    Crosby County is a rural county in northwestern Texas known for its agricultural economy and location on the South Plains region.
  • B. Yoakum County
    Yoakum County is a rural county in western Texas known for its agriculture and oil production.
  • C. Alfalfa County
    Alfalfa County is a rural county in northwestern Oklahoma known for its agricultural economy and small-town communities.
  • D. Llano County
    Llano County is a rural county in central Texas known for its scenic Hill Country landscapes, granite outcrops, and outdoor recreation around lakes and rivers.
  • E. Ballard County
    Ballard County is a rural county in far western Kentucky, located within the Jackson Purchase region along the Mississippi River.
  • 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_69d806aee7308190b70a237ba2a6e3e1 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98cf28c9c819080d7b42d20f579d1 completed April 10, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6ff1ebf648190a27d11b3dc494446 completed May 3, 2026, 7:54 a.m.
Created at: April 9, 2026, 9:18 p.m.