Triple

T13434751
Position Surface form Disambiguated ID Type / Status
Subject Last Days E320200 entity
Predicate producer P490 FINISHED
Object Dany Wolf E227099 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: Dany Wolf | Statement: [Last Days, producer, Dany Wolf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dany Wolf
Context triple: [Last Days, producer, Dany Wolf]
  • A. Dany Wolf chosen
    Dany Wolf is a film producer known for his work on notable projects including the acclaimed adaptation of August Wilson’s play "Ma Rainey’s Black Bottom."
  • B. Jeffrey Wolf
    Jeffrey Wolf is a film editor known for his work on feature films such as the 1996 drama "Beautiful Girls."
  • C. Daniel Wolf
    Daniel Wolf was an American art dealer and collector known for his influential work in the photography art market and his marriage to artist and architect Maya Lin.
  • D. Ben Seresin
    Ben Seresin is a New Zealand-born cinematographer known for his work on large-scale action and blockbuster films such as Godzilla vs. Kong, World War Z, and Transformers: Revenge of the Fallen.
  • E. Rob Wasserman
    Rob Wasserman was an American Grammy-winning bassist and composer known for his innovative solo work and collaborations with artists such as Bob Weir, Lou Reed, and Elvis Costello.
  • 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_69d80761e6cc8190a90c844589998ecc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaee29fec81908b07b4fca2922242 completed April 12, 2026, 2:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7461f44b08190802290db7a4e6a5e completed May 3, 2026, 12:57 p.m.
Created at: April 9, 2026, 9:40 p.m.