Triple

T5273721
Position Surface form Disambiguated ID Type / Status
Subject Mulan (1998 film score) E119322 entity
Predicate associatedLyricist P1360 FINISHED
Object David Zippel E252694 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: David Zippel | Statement: [Mulan (1998 film score), associatedLyricist, David Zippel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: David Zippel
Context triple: [Mulan (1998 film score), associatedLyricist, David Zippel]
  • A. David Zippel chosen
    David Zippel is an American lyricist known for his work on Broadway musicals and animated films, including contributions to productions like "City of Angels" and Disney's "Hercules."
  • B. Phil Zimmermann
    Phil Zimmermann is an American cryptographer best known as the creator of Pretty Good Privacy (PGP), a widely used email encryption software that helped popularize strong cryptography for the public.
  • C. Michael Lehmann
    Michael Lehmann is an American film and television director best known for the dark comedy "Heathers" and various other Hollywood comedies.
  • D. Robert Scheifler
    Robert Scheifler is a computer scientist best known for leading the development of the X Window System at MIT.
  • E. Vaughan Pratt
    Vaughan Pratt is a computer scientist known for his contributions to algorithms and formal methods, including co-developing the Knuth–Morris–Pratt string-searching algorithm.
  • 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_69bd446c38e081908cdaf113bdf86790 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7c22a29081908a022847e61af8a9 completed March 20, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf06d1f874819098a9b99f8bb9f654 completed March 21, 2026, 9 p.m.
Created at: March 20, 2026, 1:51 p.m.