Triple

T9970108
Position Surface form Disambiguated ID Type / Status
Subject Venom E196181 entity
Predicate producer P490 FINISHED
Object Matt Tolmach E597393 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: Matt Tolmach | Statement: [Venom, producer, Matt Tolmach]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matt Tolmach
Context triple: [Venom, producer, Matt Tolmach]
  • A. Matt Tolmach chosen
    Matt Tolmach is an American film producer and former Sony Pictures executive best known for his work on the Spider-Man franchise.
  • B. Russ Titelman
    Russ Titelman is an American record producer and songwriter known for his work with major artists across rock and pop music, including collaborations with the likes of Eric Clapton and George Harrison.
  • C. Jeff Kodosky
    Jeff Kodosky is an American engineer and co-founder of National Instruments, best known as the "father of LabVIEW" for creating the influential graphical programming environment.
  • D. Johnny Gandelsman
    Johnny Gandelsman is a Grammy-winning violinist and producer known for his work with ensembles like Brooklyn Rider and the Silk Road Ensemble, as well as for his innovative solo projects.
  • E. Ben D. Waisbren
    Ben D. Waisbren is a film producer known for financing and producing major studio and independent movies.
  • 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_69ca82eea2b88190a0e511d21a31f386 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb7b7ea9881908a56f11e2e446dd0 completed April 2, 2026, 12:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69d71c3fa4b88190be4ce7b64335a99f completed April 9, 2026, 3:25 a.m.
Created at: March 30, 2026, 8:48 p.m.