Triple

T1035815
Position Surface form Disambiguated ID Type / Status
Subject Irving E22358 entity
Predicate adjacentTo P224 FINISHED
Object Coppell E27019 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: Coppell | Statement: [Irving, adjacentTo, Coppell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Coppell
Context triple: [Irving, adjacentTo, Coppell]
  • A. Coppell chosen
    Coppell is a suburban city in the Dallas–Fort Worth metropolitan area known for its affluent residential neighborhoods and strong public school system.
  • B. Duncanville
    Duncanville is a suburban city in the Dallas–Fort Worth metropolitan area of North Texas.
  • C. Farmers Branch
    Farmers Branch is a suburban city in the Dallas–Fort Worth metropolitan area known for its residential neighborhoods, parks, and proximity to Dallas.
  • D. Rowlett
    Rowlett is a suburban city in the Dallas–Fort Worth metropolitan area of Texas, known for its location along Lake Ray Hubbard and family-oriented residential communities.
  • E. Grand Prairie
    Grand Prairie is a mid-sized suburban city in the Dallas–Fort Worth metropolitan area known for its family attractions, parks, and growing residential 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_69a493d848848190aed4011b34b2e8d3 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b816272c8190a12e470c4d4ebcf9 completed March 1, 2026, 10:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69adc977276881908405e2411eb14fa1 completed March 8, 2026, 7:09 p.m.
Created at: March 1, 2026, 7:41 p.m.