Triple

T17305855
Position Surface form Disambiguated ID Type / Status
Subject Martin Lawrence E420162 entity
Predicate notableWork P4 FINISHED
Object Boomerang E231104 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: Boomerang | Statement: [Martin Lawrence, notableWork, Boomerang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Boomerang
Context triple: [Martin Lawrence, notableWork, Boomerang]
  • A. Boomerang
    Boomerang is a television network known for airing classic and contemporary animated programming, particularly cartoons from the Warner Bros. and Hanna-Barbera libraries.
  • B. Boomerang chosen
    Boomerang is a 1992 romantic comedy film starring Eddie Murphy that follows a suave advertising executive whose womanizing ways are challenged when he meets his match.
  • C. Boomerang
    "Boomerang" is a 1998 puzzle-platform video game developed by The Creatures that features boomerang-based mechanics and environmental challenges.
  • D. Boomerang
    Boomerang is a steel shuttle roller coaster known for its forward-and-backward looping layout, operating at the Worlds of Fun amusement park in Kansas City, Missouri.
  • E. Boomerang
    "Boomerang" is a 2015 French drama film directed by François Favrat, in which François Cluzet stars in a story about a man uncovering long-buried family secrets.
  • 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_69d889d22b848190a4663d0b8f8f76e7 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e438ff3ee08190ab4c44a22f86b38b completed April 19, 2026, 2:07 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0180e0c1b881908aa2b6b4d8ac04b6 completed May 11, 2026, 7:10 a.m.
Created at: April 10, 2026, 5:43 a.m.