Triple

T4700789
Position Surface form Disambiguated ID Type / Status
Subject KDAL E104263 entity
Predicate locatedInCity P40 FINISHED
Object Dallas E370 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: Dallas | Statement: [KDAL, locatedInCity, Dallas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dallas
Context triple: [KDAL, locatedInCity, Dallas]
  • A. Dallas
    Dallas is a small city in Paulding County, Georgia, known for its historic downtown and location within the state's mineral-rich Georgia Gold Belt region.
  • B. Dallas
    Dallas is the early series of United States Supreme Court case reports compiled by Alexander J. Dallas, covering decisions from the late 18th century before the official U.S. Reports numbering began.
  • C. Dallas, Texas chosen
    Dallas, Texas is a major metropolitan city in northern Texas known for its role as a commercial and cultural hub, particularly in finance, technology, and telecommunications.
  • D. Houston
    Houston is a major U.S. metropolis known for its energy industry, NASA’s Johnson Space Center, and its diverse, rapidly growing population.
  • E. Houston
    Houston is a village in Renfrewshire, Scotland, known for its historic conservation area and role as a commuter settlement near Glasgow.
  • 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_69bd43e9b88481908582103dcadff3d9 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd63cd447081908120ee1691009982 completed March 20, 2026, 3:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69bef7d61c988190ae814cef9e726ae6 completed March 21, 2026, 7:56 p.m.
Created at: March 20, 2026, 1:17 p.m.