Triple

T11732349
Position Surface form Disambiguated ID Type / Status
Subject Babel (film score) E278927 entity
Predicate hasPart P35 FINISHED
Object “Tazarine”
“Tazarine” is a musical piece from Gustavo Santaolalla’s score for the film *Babel*, reflecting the movie’s atmospheric and cross-cultural soundscape.
 E942229 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: “Tazarine” | Statement: [Babel (film score), hasPart, “Tazarine”]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: “Tazarine”
Context triple: [Babel (film score), hasPart, “Tazarine”]
  • A. Tamzine
    Tamzine is a small British fishing boat famed for taking part in the 1940 Dunkirk evacuation as one of the celebrated "Little Ships."
  • B. Taze
    Taze is the middle name of Charles Taze Russell, the American religious leader who founded the Bible Student movement and was an early influence on Jehovah’s Witnesses.
  • C. Taznatit
    Taznatit is a Berber language whose features have influenced the development and structure of the Korandje language.
  • D. Trenzalore
    Trenzalore is a planet in the Doctor Who universe best known as the site of a pivotal, prophesied conflict in the Doctor’s timeline.
  • E. Zardoz
    Zardoz is a 1974 science fiction film directed by John Boorman, known for its surreal, dystopian vision and starring Sean Connery in one of his most unconventional roles.
  • 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: “Tazarine”
Triple: [Babel (film score), hasPart, “Tazarine”]
Generated description
“Tazarine” is a musical piece from Gustavo Santaolalla’s score for the film *Babel*, reflecting the movie’s atmospheric and cross-cultural soundscape.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: “Tazarine”
Target entity description: “Tazarine” is a musical piece from Gustavo Santaolalla’s score for the film *Babel*, reflecting the movie’s atmospheric and cross-cultural soundscape.
  • A. Tamzine
    Tamzine is a small British fishing boat famed for taking part in the 1940 Dunkirk evacuation as one of the celebrated "Little Ships."
  • B. Taze
    Taze is the middle name of Charles Taze Russell, the American religious leader who founded the Bible Student movement and was an early influence on Jehovah’s Witnesses.
  • C. Taznatit
    Taznatit is a Berber language whose features have influenced the development and structure of the Korandje language.
  • D. Trenzalore
    Trenzalore is a planet in the Doctor Who universe best known as the site of a pivotal, prophesied conflict in the Doctor’s timeline.
  • E. Zardoz
    Zardoz is a 1974 science fiction film directed by John Boorman, known for its surreal, dystopian vision and starring Sean Connery in one of his most unconventional roles.
  • 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_69d6aaffec6881908bead509e8621742 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4d94de08190a7184cf26d8cb94e completed April 10, 2026, 7:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef83f98fc481908015df3c4e5d7ed3 completed April 27, 2026, 3:42 p.m.
NEDg Description generation batch_69ef9b68309081909f3f614efeeb2ab1 completed April 27, 2026, 5:22 p.m.
NED2 Entity disambiguation (via description) batch_69efd6aba82c81909ff22e6b26db3cfe completed April 27, 2026, 9:35 p.m.
Created at: April 8, 2026, 9:41 p.m.