Triple

T6693614
Position Surface form Disambiguated ID Type / Status
Subject Dallas urban area E152689 entity
Predicate hasSuburb P747 FINISHED
Object Euless E111319 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: Euless | Statement: [Dallas urban area, hasSuburb, Euless]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Euless
Context triple: [Dallas urban area, hasSuburb, Euless]
  • A. Euless, Texas chosen
    Euless, Texas is a suburban city in Tarrant County that forms part of the Mid-Cities region between Dallas and Fort Worth.
  • B. Duncanville
    Duncanville is a suburban city in the Dallas–Fort Worth metropolitan area of North Texas.
  • C. 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.
  • D. Wimberley
    Wimberley is a small, scenic town in central Texas known for its picturesque Hill Country landscapes, swimming holes, and artsy, tourist-friendly downtown.
  • 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 (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_69c6880687b08190805278b504d1c92c completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6b1955e448190adbfed7dc28f8c52 completed March 27, 2026, 4:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7eeb127248190bbee7a9f69c2b980 completed March 28, 2026, 3:07 p.m.
Created at: March 27, 2026, 2:05 p.m.