Triple

T12423512
Position Surface form Disambiguated ID Type / Status
Subject I Want to Live! E296838 entity
Predicate screenwriter P2831 FINISHED
Object Don Mankiewicz E308536 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: Don Mankiewicz | Statement: [I Want to Live!, screenwriter, Don Mankiewicz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Don Mankiewicz
Context triple: [I Want to Live!, screenwriter, Don Mankiewicz]
  • A. Don Mankiewicz chosen
    Don Mankiewicz was an American screenwriter and novelist known for his work in film and television during the mid-20th century.
  • B. Tom Mankiewicz
    Tom Mankiewicz was an American screenwriter, director, and producer best known for his work on several James Bond films and the script for the 1978 film "Superman."
  • C. Ben Mankiewicz
    Ben Mankiewicz is an American television host and film critic best known as a longtime presenter and commentator on Turner Classic Movies (TCM).
  • D. Josh Mankiewicz
    Josh Mankiewicz is an American journalist best known as a longtime correspondent for NBC's newsmagazine program "Dateline NBC."
  • E. Herman J. Mankiewicz
    Herman J. Mankiewicz was an American screenwriter and wit best known for co-writing the landmark film "Citizen Kane" and for his influential work in Hollywood’s Golden Age.
  • 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_69d6ada0640c81908c061d7fb3d47786 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d7b6bd08190b30beba393a5b1e7 completed April 10, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64b97df9081909b281ed6c568fa37 completed May 2, 2026, 7:08 p.m.
Created at: April 8, 2026, 9:55 p.m.