Triple

T14730525
Position Surface form Disambiguated ID Type / Status
Subject Adventures in Babysitting E346058 entity
Predicate producer P490 FINISHED
Object Lynda Obst E159259 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: Lynda Obst | Statement: [Adventures in Babysitting, producer, Lynda Obst]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lynda Obst
Context triple: [Adventures in Babysitting, producer, Lynda Obst]
  • A. Lynda Obst chosen
    Lynda Obst is an American film producer and author known for her work on major Hollywood films, including the science fiction epic "Interstellar."
  • B. Lynda Bernhard
    Lynda Bernhard is known as the wife of American film producer Harvey Bernhard.
  • C. Lucinda Jenney
    Lucinda Jenney is an American character actress known for her versatile supporting roles in films and television since the 1980s.
  • D. Lynda Petty
    Lynda Petty was the longtime wife of NASCAR legend Richard Petty and a prominent figure in the racing community known for her charitable work and support of the Petty family’s motorsports legacy.
  • E. Lisa Reisert
    Lisa Reisert is the resourceful and determined protagonist of the thriller film "Red Eye," who becomes entangled in a high-stakes assassination plot during a red-eye flight.
  • 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_69d822e5911c8190ba589f957dbd9ba7 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec26311c8819093a81ff0fa43b33b completed April 14, 2026, 10:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdfb89ea388190b356df74e36023f7 completed May 8, 2026, 3:04 p.m.
Created at: April 10, 2026, 1:29 a.m.