Triple

T3250487
Position Surface form Disambiguated ID Type / Status
Subject The Chair E68164 entity
Predicate executiveProducer P7225 FINISHED
Object Amanda Peet E81876 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: Amanda Peet | Statement: [The Chair, executiveProducer, Amanda Peet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amanda Peet
Context triple: [The Chair, executiveProducer, Amanda Peet]
  • A. Amanda Peet chosen
    Amanda Peet is an American actress known for her work in films like "The Whole Nine Yards" and television series such as "Studio 60 on the Sunset Strip" and "Togetherness."
  • B. Parker Posey
    Parker Posey is an American actress known for her quirky, offbeat roles in independent films of the 1990s, earning her the nickname "Queen of the Indies."
  • C. Judy Greer
    Judy Greer is an American actress known for her versatile supporting roles in film and television, including appearances in major franchises like the Marvel Cinematic Universe.
  • D. Alison Lohman
    Alison Lohman is an American actress known for her roles in films such as Big Fish, White Oleander, and Drag Me to Hell.
  • E. Leslie Mann
    Leslie Mann is an American actress known for her comedic and dramatic roles in films such as "The 40-Year-Old Virgin," "Knocked Up," and "This Is 40."
  • 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_69ad858e4c708190aa31d486cfee8a6a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaf40f7908190a450c3136fccb020 completed March 8, 2026, 5:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69b31a67d0a08190853699b0aa39b359 completed March 12, 2026, 7:56 p.m.
Created at: March 8, 2026, 3:09 p.m.