Triple

T16619783
Position Surface form Disambiguated ID Type / Status
Subject Clifton McNeely E403792 entity
Predicate workLocation P7 FINISHED
Object Pampa, Texas E920796 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: Pampa, Texas | Statement: [Clifton McNeely, workLocation, Pampa, Texas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pampa, Texas
Context triple: [Clifton McNeely, workLocation, Pampa, Texas]
  • A. Pampa, Texas chosen
    Pampa, Texas is a small city in the Texas Panhandle known historically for its role in the oil and gas industry and as a regional hub for agriculture and transportation.
  • B. Pantego, Texas
    Pantego, Texas is a small incorporated town in the Dallas–Fort Worth metropolitan area known for its suburban residential character and proximity to Arlington.
  • C. Palmer, Texas
    Palmer, Texas is a small town located in Ellis County within the Dallas–Fort Worth metropolitan area.
  • D. Purves, Texas
    Purves, Texas is a small rural unincorporated community located in Erath County in north-central Texas.
  • E. Mount Pleasant, Texas
    Mount Pleasant, Texas is a small city in northeastern Texas that serves as a regional commercial and cultural hub within the Ark-La-Tex area.
  • 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_69d883897eb481909eaaa088ba9918d9 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3754c934c8190a0a8ddd747681aa7 completed April 18, 2026, 12:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a007db0b4348190beb573bc3df98125 completed May 10, 2026, 12:44 p.m.
Created at: April 10, 2026, 5:17 a.m.