Triple

T14969448
Position Surface form Disambiguated ID Type / Status
Subject Hockley County E373277 entity
Predicate hasBorderWith P224 FINISHED
Object Cochran County E394235 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: Cochran County | Statement: [Hockley County, hasBorderWith, Cochran County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cochran County
Context triple: [Hockley County, hasBorderWith, Cochran County]
  • A. Cochran County chosen
    Cochran County is a sparsely populated rural county in far west Texas known for its agriculture and location along the New Mexico border.
  • B. Waller County
    Waller County is a county in southeastern Texas that forms part of the greater Houston metropolitan region.
  • C. Donley County
    Donley County is a rural county in the Texas Panhandle known for its ranching heritage, small communities, and wide-open High Plains landscapes.
  • D. Ringgold County
    Ringgold County is a rural county located in the southwestern part of the U.S. state of Iowa.
  • E. Parmer County
    Parmer County is a rural county in the western Texas Panhandle known for its agriculture-based economy and small, close-knit communities.
  • 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_69d85ccbbcd48190acb56e7cf104d8ad completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded6e44cb0819096e09f8026ef8174 completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69fef888a7988190837f3f4b8d340e04 completed May 9, 2026, 9:04 a.m.
Created at: April 10, 2026, 2:49 a.m.