Triple

T6579200
Position Surface form Disambiguated ID Type / Status
Subject My Fair Lady (film) E157247 entity
Predicate stars P1956 FINISHED
Object Stanley Holloway E205504 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: Stanley Holloway | Statement: [My Fair Lady (film), stars, Stanley Holloway]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stanley Holloway
Context triple: [My Fair Lady (film), stars, Stanley Holloway]
  • A. Stanley Holloway chosen
    Stanley Holloway was an English actor and comic entertainer best known for his character roles on stage and in films such as "My Fair Lady" and numerous Ealing comedies.
  • B. Kenneth Williams
    Kenneth Williams was a celebrated British comic actor and raconteur, best known for his roles in the "Carry On" films and his distinctive, witty presence on radio and television panel shows.
  • C. Ron Todd
    Ron Todd was a prominent British trade union leader who served as a key figure in the labor movement during the late 20th century.
  • D. Ron Todd
    Ron Todd is an American politician who served as the Kansas Insurance Commissioner before Kathleen Sebelius.
  • E. Peter Ustinov
    Peter Ustinov was a British actor, writer, and director renowned for his wit, versatility, and memorable character roles in film and television.
  • 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_69c6882b3a108190b3a9eb343ae4162c completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ae8dad608190b4708368a7af6e5d completed March 27, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d56fe8f08190ad30773f29b207c5 completed March 27, 2026, 7:07 p.m.
Created at: March 27, 2026, 1:54 p.m.