Triple

T9117235
Position Surface form Disambiguated ID Type / Status
Subject Pretty Woman E218750 entity
Predicate cinematographyBy P1953 FINISHED
Object Charles Minsky E543345 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: Charles Minsky | Statement: [Pretty Woman, cinematographyBy, Charles Minsky]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Charles Minsky
Context triple: [Pretty Woman, cinematographyBy, Charles Minsky]
  • A. Charles Minsky chosen
    Charles Minsky is an American cinematographer known for his work on numerous Hollywood films, particularly romantic comedies.
  • B. Morton Minsky
    Morton Minsky was a member of the Minsky family associated with the famous Minsky's Burlesque theater circuit in early 20th-century New York entertainment.
  • C. Henry Minsky
    Henry Minsky is the son of artificial intelligence pioneer Marvin Minsky and is known as a software engineer and technologist.
  • D. Henry Pincus
    Henry Pincus is known primarily as the son of prominent American financier and private equity pioneer Lionel Pincus.
  • E. Milton Shulman
    Milton Shulman was a Canadian-born British theatre, film, and television critic best known for his long tenure at the London Evening Standard and his influential writings on popular culture.
  • 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_69ca83dc94ac8190b9ef42684d36ff39 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca8a5e2ac8190b602ef0c77deb2fa completed April 1, 2026, 5:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0544c06ec8190917707d75db7e9c5 completed April 3, 2026, 11:59 p.m.
Created at: March 30, 2026, 7:17 p.m.