Triple

T13508633
Position Surface form Disambiguated ID Type / Status
Subject Autumn E321078 entity
Predicate mainCharacter P1183 FINISHED
Object Daniel Gluck
Daniel Gluck is a central fictional character in Ali Smith’s novel "Autumn," around whom themes of memory, time, and friendship are explored.
E1050372 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: Daniel Gluck | Statement: [Autumn, mainCharacter, Daniel Gluck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daniel Gluck
Context triple: [Autumn, mainCharacter, Daniel Gluck]
  • A. Martin Weinberg
    Martin Weinberg is a sociologist known for his influential research on human sexuality, sexual deviance, and the social construction of sexual norms.
  • B. Daniel W. Herzog
    Daniel W. Herzog is an American Anglican bishop best known for serving as the Bishop of the Episcopal Diocese of Albany in New York.
  • C. Daniel Fuchs
    Daniel Fuchs was an American novelist and screenwriter known for his Brooklyn-set fiction and acclaimed Hollywood screenplays, including several classic film noirs.
  • D. Richard Rochberg
    Richard Rochberg is an American mathematician known for his contributions to harmonic analysis and operator theory.
  • E. Richard Landau
    Richard Landau was an American screenwriter known for his work on mid-20th-century genre films and television, particularly in science fiction and crime.
  • 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: Daniel Gluck
Triple: [Autumn, mainCharacter, Daniel Gluck]
Generated description
Daniel Gluck is a central fictional character in Ali Smith’s novel "Autumn," around whom themes of memory, time, and friendship are explored.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Daniel Gluck
Target entity description: Daniel Gluck is a central fictional character in Ali Smith’s novel "Autumn," around whom themes of memory, time, and friendship are explored.
  • A. Martin Weinberg
    Martin Weinberg is a sociologist known for his influential research on human sexuality, sexual deviance, and the social construction of sexual norms.
  • B. Daniel W. Herzog
    Daniel W. Herzog is an American Anglican bishop best known for serving as the Bishop of the Episcopal Diocese of Albany in New York.
  • C. Daniel Fuchs
    Daniel Fuchs was an American novelist and screenwriter known for his Brooklyn-set fiction and acclaimed Hollywood screenplays, including several classic film noirs.
  • D. Richard Rochberg
    Richard Rochberg is an American mathematician known for his contributions to harmonic analysis and operator theory.
  • E. Richard Landau
    Richard Landau was an American screenwriter known for his work on mid-20th-century genre films and television, particularly in science fiction and crime.
  • 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_69d807629d6c8190998f1b9bb12d2ed0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaf85a74081909eb08751fc55ce8f completed April 12, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f77f8239c481909faf5a9c403b55f2 completed May 3, 2026, 5:01 p.m.
NEDg Description generation batch_69f7800caaf0819085e553f96a9f99cf completed May 3, 2026, 5:04 p.m.
NED2 Entity disambiguation (via description) batch_69f78089050c81909943164d1a41a37f completed May 3, 2026, 5:06 p.m.
Created at: April 9, 2026, 9:43 p.m.