Triple

T15546362
Position Surface form Disambiguated ID Type / Status
Subject Garza County E370619 entity
Predicate countySeat P383 FINISHED
Object Post, Texas E791534 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: Post, Texas | Statement: [Garza County, countySeat, Post, Texas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Post, Texas
Context triple: [Garza County, countySeat, Post, Texas]
  • A. Post, Texas chosen
    Post, Texas is a small West Texas city in Garza County known historically as a planned community founded by cereal magnate C.W. Post.
  • B. Spring, Texas
    Spring, Texas is a suburban community in the Greater Houston area known for its residential neighborhoods, proximity to major employment centers, and attractions like Old Town Spring.
  • C. Tool, Texas
    Tool, Texas is a small lakeside city in Henderson County known for its proximity to Cedar Creek Reservoir and its rural, residential character.
  • D. Navasota, Texas
    Navasota, Texas is a small city in Grimes County that serves as a historic railroad and commercial hub within the Greater Houston metropolitan area.
  • E. Combine, Texas
    Combine, Texas is a small rural city in the Dallas–Fort Worth metropolitan area known for its quiet, country living and proximity to both Kaufman and Dallas counties.
  • 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_69d85cc521a08190921fb50319dddc34 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04a9073948190b6e9cf504aacc7cf completed April 16, 2026, 2:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff455a38188190a593c70be09d6103 completed May 9, 2026, 2:31 p.m.
Created at: April 10, 2026, 4:07 a.m.