Triple

T4511281
Position Surface form Disambiguated ID Type / Status
Subject Texas Triangle E102058 entity
Predicate containsCity P294 FINISHED
Object Garland E9807 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: Garland | Statement: [Texas Triangle, containsCity, Garland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Garland
Context triple: [Texas Triangle, containsCity, Garland]
  • A. Garland chosen
    Garland is a large suburban city in the Dallas–Fort Worth metropolitan area known for its diverse community and mixed residential, commercial, and industrial character.
  • B. Garland Greene
    Garland Greene is a notorious, eerily soft-spoken serial killer character from the action film "Con Air," portrayed by Steve Buscemi.
  • C. Doc Boone
    Doc Boone is the hard-drinking yet compassionate frontier doctor character from John Ford’s classic Western film "Stagecoach."
  • D. Crawford
    Crawford is a Scottish-origin surname borne by numerous notable figures across politics, sports, arts, and entertainment.
  • E. Kilmer
    Kilmer is the surname of American actor Val Kilmer, known for his roles in films such as "Top Gun," "The Doors," and "Batman Forever."
  • 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_69bd43d6251c81909deecce3e6e9d69c completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd571412788190a374abd1e05519e4 completed March 20, 2026, 2:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd7f875c4c81909e67d44b605816c2 completed March 20, 2026, 5:10 p.m.
Created at: March 20, 2026, 1:01 p.m.