Triple

T3858615
Position Surface form Disambiguated ID Type / Status
Subject Big Daddy E90080 entity
Predicate starring P1507 FINISHED
Object Leslie Mann E183575 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: Leslie Mann | Statement: [Big Daddy, starring, Leslie Mann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leslie Mann
Context triple: [Big Daddy, starring, Leslie Mann]
  • A. Leslie Mann chosen
    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."
  • B. Amanda Peet
    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."
  • C. 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.
  • D. 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.
  • E. 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."
  • 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_69aed95b3c088190a8f85d19e6070599 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeec1e68f88190941c39221486f6ae completed March 9, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5283ccf68819086c6349ceb71f099 completed March 14, 2026, 9:19 a.m.
Created at: March 9, 2026, 3:19 p.m.