Triple

T6180643
Position Surface form Disambiguated ID Type / Status
Subject George Axelrod E137932 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: [George Axelrod, notableWork, Bus Stop]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bus Stop
Context triple: [George Axelrod, 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. 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.
  • C. Bank station
    Bank station is a major central London interchange on the Underground and Docklands Light Railway network, serving as a key hub in the City of London financial district.
  • D. Autobuses del Norte station
    Autobuses del Norte station is a Mexico City Metro stop that provides direct access to the city’s main northern intercity bus terminal, serving as a key hub for regional and long-distance travel.
  • E. Benchill tram stop
    Benchill tram stop is a light-rail station on Greater Manchester’s Metrolink network serving the Benchill area of Wythenshawe.
  • 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_69c008a80f748190ba3d07ffc81acb29 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c060fdf7ac8190a0e887907ec9a922 completed March 22, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69c141bf3f4081909849e38d322da251 completed March 23, 2026, 1:35 p.m.
Created at: March 22, 2026, 4:18 p.m.