Triple

T20597094
Position Surface form Disambiguated ID Type / Status
Subject BNSF Bellingham Subdivision E506077 entity
Predicate servesCommunity P82 FINISHED
Object Blaine NE NERFINISHED

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: Blaine | Statement: [BNSF Bellingham Subdivision, servesCommunity, Blaine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Blaine
Context triple: [BNSF Bellingham Subdivision, servesCommunity, Blaine]
  • A. Blaine chosen
    Blaine is a small coastal city in northwestern Washington State, located near the Canadian border.
  • B. Blaine
    Blaine is a surname most notably associated with James G. Blaine, a prominent 19th-century American statesman and politician.
  • C. Blaine
    Blaine is the laid-back, surfing-obsessed teenage protagonist of the 1993 comedy film "Airborne," known for his inline skating skills and culture clash after moving from California to Cincinnati.
  • D. Leland
    Leland is a masculine given name of English origin, historically associated with figures such as American industrialist and Stanford University founder Leland Stanford.
  • E. Leland
    Leland is a residential neighborhood located within the city of Compton, California.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4ba6ae88190af871e1f9522c704 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6aa1d15b08190a720fc7cefbf333e completed April 20, 2026, 10:35 p.m.
Created at: April 16, 2026, 11:40 a.m.