Triple

T15625071
Position Surface form Disambiguated ID Type / Status
Subject Calendar Girls E375657 entity
Predicate editedBy P1954 FINISHED
Object Michael Parker E535835 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: Michael Parker | Statement: [Calendar Girls, editedBy, Michael Parker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Parker
Context triple: [Calendar Girls, editedBy, Michael Parker]
  • A. Michael Parker
    Michael Parker is a literary scholar and editor known for his work on classic novels such as Edith Wharton's "The House of Mirth."
  • B. Michael Parker chosen
    Michael Parker is a film editor best known for his work on the British comedy-drama "Made in Dagenham."
  • C. Ian Parker
    Ian Parker is a British keyboardist best known for his work with the rock band The Hollies and various other prominent artists.
  • D. James Parker
    James Parker was a British Labour politician and trade unionist active in the early 20th century.
  • E. Michael Parkhurst
    Michael Parkhurst is an American former professional soccer defender best known for his standout MLS career and leadership roles with clubs like New England Revolution, Columbus Crew SC, and Atlanta United FC, as well as appearances for the U.S. national team.
  • 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_69d85cd035a48190b73d5579ab73969a completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e9e5e248190ae54cda1fde51efb completed April 16, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbba9fb08190b800af317f0c9abf completed May 10, 2026, 1:13 a.m.
Created at: April 10, 2026, 4:14 a.m.