Triple

T14535579
Position Surface form Disambiguated ID Type / Status
Subject Larry Miller E341034 entity
Predicate notableWork P4 FINISHED
Object Pretty Woman E218750 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: Pretty Woman | Statement: [Larry Miller, notableWork, Pretty Woman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pretty Woman
Context triple: [Larry Miller, notableWork, Pretty Woman]
  • A. Pretty Woman chosen
    Pretty Woman is a 1990 romantic comedy film starring Julia Roberts and Richard Gere, widely known for its modern Cinderella-style love story set in Los Angeles.
  • B. Oh, Pretty Woman
    "Oh, Pretty Woman" is a 1964 rock and roll song by Roy Orbison, famous for its iconic guitar riff and Orbison’s powerful vocal performance.
  • C. What a Woman Wants
    "What a Woman Wants" is a musical number from the stage adaptation of the film *Kinky Boots*, featuring lyrics by Cyndi Lauper that explores themes of desire, identity, and empowerment.
  • D. That’s Why I Love You
    "That’s Why I Love You" is a song featured on SiR’s R&B album *Chasing Summer*.
  • E. One from the Heart
    One from the Heart is a 1982 romantic musical film directed by Francis Ford Coppola, noted for its stylized visuals, elaborate studio sets, and troubled production and release.
  • 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_69d822dac79c8190a84a073f3cbaced5 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb1b9d39881908c7a3a5b17d432af completed April 14, 2026, 9:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd7a589d488190b4a192f33d11092d completed May 8, 2026, 5:53 a.m.
Created at: April 10, 2026, 1:22 a.m.