Triple

T6335532
Position Surface form Disambiguated ID Type / Status
Subject GM Arlington Assembly Plant E142480 entity
Predicate city P40 FINISHED
Object Arlington E423109 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: Arlington | Statement: [GM Arlington Assembly Plant, city, Arlington]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arlington
Context triple: [GM Arlington Assembly Plant, city, Arlington]
  • A. Arlington chosen
    Arlington is a major city in the Dallas–Fort Worth metropolitan area known for its sports stadiums, entertainment venues, and rapidly growing population.
  • B. Arlington
    Arlington is the middle name of American poet Edwin Arlington Robinson, after whom he is commonly known.
  • C. Arlington
    Arlington is a suburban town in Middlesex County, Massachusetts, located northwest of Boston and known for its historic sites and residential character.
  • D. Arlington
    Arlington is a small city in northern Washington State, United States, situated in Snohomish County north of Seattle.
  • E. Arlington
    Arlington is a historic antebellum house and garden estate in Birmingham, Alabama, preserved as a museum showcasing 19th-century Southern architecture and life.
  • 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_69c008d4d8e88190ad301c05b08722ac completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0654a88a881908d5cb2aa7f22c4c7 completed March 22, 2026, 9:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d50184a081908286d92166fd1c00 completed March 27, 2026, 7:05 p.m.
Created at: March 22, 2026, 4:30 p.m.