Triple

T14044505
Position Surface form Disambiguated ID Type / Status
Subject The Weepies E337921 entity
Predicate hasCreativeDirector P24221 FINISHED
Object Steve Tannen E1075948 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: Steve Tannen | Statement: [The Weepies, hasCreativeDirector, Steve Tannen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Steve Tannen
Context triple: [The Weepies, hasCreativeDirector, Steve Tannen]
  • A. Steve Tannen chosen
    Steve Tannen is an American singer-songwriter best known as one half of the indie-folk duo The Weepies.
  • B. Tom Langer
    Tom Langer is an individual notable enough to be recognized as a bearer of the surname Langer, though specific widely known public details about him are not clearly established.
  • C. Maury Winetrobe
    Maury Winetrobe is a film editor best known for his work on classic Hollywood productions such as "Pocketful of Miracles."
  • D. Darren Silverman
    Darren Silverman is the hapless, love-struck protagonist of the comedy film "Saving Silverman," whose friends scheme to rescue him from a disastrous relationship.
  • E. Joe Swanson
    Joe Swanson is a paraplegic, tough but good-hearted police officer and one of Peter Griffin’s closest friends in the animated sitcom "Family Guy."
  • 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_69d81c664e48819088cbd8f433aeffe5 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de312b94308190bd0961f5bc719c7b completed April 14, 2026, 12:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcb65c1a90819097754497f07f5312 completed May 7, 2026, 3:57 p.m.
Created at: April 9, 2026, 10:20 p.m.