Triple

T12412739
Position Surface form Disambiguated ID Type / Status
Subject Buddy Adler E296556 entity
Predicate notableWork P4 FINISHED
Object Bus Stop E92895 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: Bus Stop | Statement: [Buddy Adler, notableWork, Bus Stop]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bus Stop
Context triple: [Buddy Adler, notableWork, Bus Stop]
  • A. Bus Stop chosen
    Bus Stop is a 1956 romantic comedy-drama film starring Marilyn Monroe as a small-town saloon singer pursued by a naive cowboy.
  • B. bus stand B
    Bus stand B is a designated boarding and alighting point for bus services operating from London Bridge bus station in central London.
  • C. Express Bus Terminal Station
    Express Bus Terminal Station is a major transportation hub in Seoul that integrates intercity bus services with multiple subway lines and extensive commercial facilities.
  • D. Satna bus stand
    Satna bus stand is the main bus terminal in Satna, Madhya Pradesh, serving as a key hub for regional and intercity road transport.
  • E. Centro bus service
    Centro bus service is the primary public transit system in the Syracuse, New York area, providing local and regional bus routes that connect neighborhoods, commercial districts, and key destinations such as Armory Square.
  • 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_69d6ad9f464c81909db36d7e96e34b9e completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d6b0f9c8190813b6fe3f97570ac completed April 10, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6348ccaf88190aeb0dfb7fe1d8dec completed May 2, 2026, 5:29 p.m.
Created at: April 8, 2026, 9:55 p.m.