Triple

T10776723
Position Surface form Disambiguated ID Type / Status
Subject Zelig E254214 entity
Predicate featuresFictionalForm P95408 FINISHED
Object documentary interviews LITERAL 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: documentary interviews | Statement: [Zelig, featuresFictionalForm, documentary interviews]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: featuresFictionalForm
Context triple: [Zelig, featuresFictionalForm, documentary interviews]
  • A. hasFictionalForm
    Indicates that an entity has a counterpart or representation that exists within a fictional or imaginary context.
  • B. featuresFictionalMusical
    Indicates that a work includes or prominently involves a fictional musical as part of its content or storyline.
  • C. featuresFictionalProgram
    Indicates that a work includes or presents a fictional program (such as a TV show, software, or in-universe broadcast) as part of its content.
  • D. featuresFictionalTechnology
    Indicates that an entity includes, depicts, or makes use of imagined or speculative technology that does not exist in reality.
  • E. featuresFictionalSport
    Indicates that a work includes or showcases a fictional sport as part of its content or setting.
  • F. None of above. chosen

Provenance (4 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_69d6aa609f008190a294200aefcb7bd5 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7329d8c908190bddad40685133ea1 completed April 9, 2026, 5:01 a.m.
PD Predicate disambiguation batch_69d6f31455648190b5c24690487b1b54 completed April 9, 2026, 12:30 a.m.
PDg Predicate description generation batch_69d6fa334b8c819082eaf8537084c323 completed April 9, 2026, 1 a.m.
Created at: April 8, 2026, 9:16 p.m.