Triple

T16656279
Position Surface form Disambiguated ID Type / Status
Subject Media Ventures E404738 entity
Predicate hasMember P10 FINISHED
Object Mark Mancina E354225 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: Mark Mancina | Statement: [Media Ventures, hasMember, Mark Mancina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mark Mancina
Context triple: [Media Ventures, hasMember, Mark Mancina]
  • A. Mark Mancina chosen
    Mark Mancina is an American composer best known for his work on film scores and soundtracks across action, animation, and adventure movies.
  • B. Jimmy Martino
    Jimmy Martino is the charming, commitment-averse bachelor who discovers he has both a son and a granddaughter in the sitcom "Grandfathered."
  • C. Michael Kamen
    Michael Kamen was an American composer and conductor renowned for his film and television scores, including major works in action cinema and acclaimed historical dramas.
  • D. Christophe Beck
    Christophe Beck is a Canadian composer best known for his film and television scores, including work on projects like "Buffy the Vampire Slayer" and various major Hollywood films.
  • E. Ron Goodwin
    Ron Goodwin was a British composer and conductor best known for his rousing film scores for war and adventure movies in the mid-20th century.
  • 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_69d8838b5fbc81908c6575c132b82e80 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37bfb2b308190bf3559df9fbb126f completed April 18, 2026, 12:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00dbf6507081909f6a49c003f9d6d6 completed May 10, 2026, 7:26 p.m.
Created at: April 10, 2026, 5:18 a.m.