Triple

T2124500
Position Surface form Disambiguated ID Type / Status
Subject Finding Nemo E46396 entity
Predicate writer P1360 FINISHED
Object David Reynolds
David Reynolds is an American screenwriter best known for his work on acclaimed animated films such as Pixar's "Finding Nemo."
 E250496 NE FINISHED

How this triple was built (4 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 Reynolds | Statement: [Finding Nemo, writer, David Reynolds]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: David Reynolds
Context triple: [Finding Nemo, writer, David Reynolds]
  • A. David Duffield
    David Duffield is an American billionaire entrepreneur and philanthropist best known for founding the enterprise software companies PeopleSoft and Workday.
  • B. David Burrows
    David Burrows is a film editor best known for his work on major animated features, including The Lego Movie.
  • C. Michael Ward
    Michael Ward was a British character actor known for his numerous supporting roles in mid-20th-century film and television comedies.
  • D. Michael Fortier
    Michael Fortier is an American former associate of Timothy McVeigh who became known for his involvement in and testimony about the 1995 Oklahoma City bombing.
  • E. David Reid
    David Reid is a film producer known for his work on major British and international feature films, including the action spy movie "Kingsman: The Secret Service."
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: David Reynolds
Triple: [Finding Nemo, writer, David Reynolds]
Generated description
David Reynolds is an American screenwriter best known for his work on acclaimed animated films such as Pixar's "Finding Nemo."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: David Reynolds
Target entity description: David Reynolds is an American screenwriter best known for his work on acclaimed animated films such as Pixar's "Finding Nemo."
  • A. David Duffield
    David Duffield is an American billionaire entrepreneur and philanthropist best known for founding the enterprise software companies PeopleSoft and Workday.
  • B. David Burrows
    David Burrows is a film editor best known for his work on major animated features, including The Lego Movie.
  • C. Michael Ward
    Michael Ward was a British character actor known for his numerous supporting roles in mid-20th-century film and television comedies.
  • D. Michael Fortier
    Michael Fortier is an American former associate of Timothy McVeigh who became known for his involvement in and testimony about the 1995 Oklahoma City bombing.
  • E. David Reid
    David Reid is a film producer known for his work on major British and international feature films, including the action spy movie "Kingsman: The Secret Service."
  • F. None of above. chosen

Provenance (5 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_69a88a1626548190ae59a5028c3baa8e completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbb55cb2c8190aab8199da3335032 completed March 7, 2026, 5:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae71ac8a0081909cbb1187513bfc56 completed March 9, 2026, 7:07 a.m.
NEDg Description generation batch_69ae759def9881909c94ed211790d741 completed March 9, 2026, 7:24 a.m.
NED2 Entity disambiguation (via description) batch_69ae7634343c819094efcb7bea49ef9e completed March 9, 2026, 7:26 a.m.
Created at: March 4, 2026, 7:44 p.m.