Triple

T10817982
Position Surface form Disambiguated ID Type / Status
Subject Culberson County E255282 entity
Predicate countySeat P383 FINISHED
Object Van Horn E338420 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: Van Horn | Statement: [Culberson County, countySeat, Van Horn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Van Horn
Context triple: [Culberson County, countySeat, Van Horn]
  • A. De la Garza
    De la Garza is the fictional Mexican family surname central to Laura Esquivel’s novel "Like Water for Chocolate," associated with the domineering matriarch Mama Elena and her daughters.
  • B. Van Horn, Texas chosen
    Van Horn, Texas is a small town in far West Texas that serves as a regional crossroads and gateway community along major highways and near the Chihuahuan Desert.
  • C. Arbuckle
    Arbuckle is a small agricultural town in California’s Sacramento Valley, known for its farming community and rural character.
  • D. Lamar
    Lamar is a surname most notably associated with Mirabeau B. Lamar, the second president of the Republic of Texas.
  • E. Lamar
    Lamar is a small city in southeastern Colorado that serves as an agricultural and transportation hub for the surrounding rural region.
  • 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_69d6aa8081448190a9324184f2bd1c26 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7344866f88190be4addb7c8020fce completed April 9, 2026, 5:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69de855799748190b51745a198daa8d0 completed April 14, 2026, 6:20 p.m.
Created at: April 8, 2026, 9:18 p.m.