Triple

T23515469
Position Surface form Disambiguated ID Type / Status
Subject Get Smart E574348 entity
Predicate screenwriter P2831 FINISHED
Object Matt Ember NE NERFINISHED

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: Matt Ember | Statement: [Get Smart, screenwriter, Matt Ember]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matt Ember
Context triple: [Get Smart, screenwriter, Matt Ember]
  • A. Matt Ember chosen
    Matt Ember is an American screenwriter best known for co-writing the 2008 comedy film adaptation of "Get Smart" and other studio comedies.
  • B. Tobias
    Tobias was a Native American man from the 17th-century Wampanoag community, known primarily through his familial connection to the Sakonnet leader Awashonks.
  • C. Tobias
    Tobias is a supporting character in the film "Magic Mike XXL," appearing as part of the ensemble surrounding the group of male strippers.
  • D. Tobias
    Tobias is the full given name of Toby Ziegler, the fictional White House Communications Director from the television series "The West Wing."
  • E. Tobias
    Tobias is a surname of likely Hebrew origin, borne by various notable individuals including the American character actor George Tobias.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245bb3dcc8190ba9a2b35972b58d0 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1aa81ab4c8190b85c8f80754020ea completed April 29, 2026, 6:51 a.m.
Created at: April 17, 2026, 6:08 p.m.