Triple

T9629519
Position Surface form Disambiguated ID Type / Status
Subject Boylston E232560 entity
Predicate hasAdjacentStation P231 FINISHED
Object Arlington E14085 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: [Boylston, hasAdjacentStation, Arlington]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arlington
Context triple: [Boylston, hasAdjacentStation, Arlington]
  • A. Arlington chosen
    Arlington is a suburban town in Middlesex County, Massachusetts, located northwest of Boston and known for its historic sites and residential character.
  • B. Arlington
    Arlington is a small city in northern Washington State, United States, situated in Snohomish County north of Seattle.
  • C. Arlington
    Arlington is a major city in the Dallas–Fort Worth metropolitan area known for its sports stadiums, entertainment venues, and rapidly growing population.
  • D. Arlington
    Arlington is the middle name of American poet Edwin Arlington Robinson, after whom he is commonly known.
  • 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_69ca848793ec8190a93a12383a754dc0 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9b00162481908f396f6b6e470d6c completed April 1, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69d189f7ea448190b9fe123589a9f3c5 completed April 4, 2026, 10 p.m.
Created at: March 30, 2026, 8:10 p.m.