Triple

T18391091
Position Surface form Disambiguated ID Type / Status
Subject Dodd City, Texas E449727 entity
Predicate hasName P744 FINISHED
Object Dodd City NE NERFINISHED

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: Dodd City | Statement: [Dodd City, Texas, hasName, Dodd City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dodd City
Context triple: [Dodd City, Texas, hasName, Dodd City]
  • A. Falls City
    Falls City is a small city in southeastern Nebraska that serves as the county seat of Richardson County and a regional hub near the Kansas and Missouri borders.
  • B. Fortrose
    Fortrose is a historic coastal town on the Black Isle in the Scottish Highlands, noted for its medieval cathedral ruins and scenic views over the Moray Firth.
  • C. Dodd City, Texas chosen
    Dodd City, Texas is a small rural town located in Fannin County in northeastern Texas.
  • D. Crosbyton
    Crosbyton is a small rural city in West Texas that serves as the administrative and commercial hub of Crosby County.
  • E. Corsicana
    Corsicana is a small city in north-central Texas known for its oil boom history and as a regional commercial and transportation hub between Dallas and Houston.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9fab8a8819086a9ddc0871715e0 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e518422e488190bd06fad72efa1641 completed April 19, 2026, 6 p.m.
Created at: April 10, 2026, 10:46 a.m.