Triple

T1978425
Position Surface form Disambiguated ID Type / Status
Subject Luis Buñuel E42968 entity
Predicate notableWork P4 FINISHED
Object Tristana
Tristana is a 1970 Spanish drama film directed by Luis Buñuel, known for its exploration of power, morality, and desire through the story of a young woman and her older guardian.
 E223574 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: Tristana | Statement: [Luis Buñuel, notableWork, Tristana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tristana
Context triple: [Luis Buñuel, notableWork, Tristana]
  • A. Katarina
    Katarina is a feminine given name, commonly used in various European cultures, that is a variant of the name Catherine.
  • B. Lina
    Lina is a Native American servant in Toni Morrison’s novel *A Mercy*, whose history of displacement and resilience reflects the novel’s themes of slavery, colonialism, and survival in 17th-century America.
  • C. Jinx
    Jinx is a Marvel Comics supervillain and member of the Hellfire Club’s Inner Circle, often associated with the mutant hunter Nimrod.
  • D. Marisa
    Marisa is a feminine given name of Latin origin, commonly used in Spanish- and Italian-speaking cultures.
  • E. Rosalinda
    Rosalinda is a feminine given name of Spanish and Italian origin, often interpreted to mean "beautiful rose."
  • 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: Tristana
Triple: [Luis Buñuel, notableWork, Tristana]
Generated description
Tristana is a 1970 Spanish drama film directed by Luis Buñuel, known for its exploration of power, morality, and desire through the story of a young woman and her older guardian.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tristana
Target entity description: Tristana is a 1970 Spanish drama film directed by Luis Buñuel, known for its exploration of power, morality, and desire through the story of a young woman and her older guardian.
  • A. Katarina
    Katarina is a feminine given name, commonly used in various European cultures, that is a variant of the name Catherine.
  • B. Lina
    Lina is a Native American servant in Toni Morrison’s novel *A Mercy*, whose history of displacement and resilience reflects the novel’s themes of slavery, colonialism, and survival in 17th-century America.
  • C. Jinx
    Jinx is a Marvel Comics supervillain and member of the Hellfire Club’s Inner Circle, often associated with the mutant hunter Nimrod.
  • D. Marisa
    Marisa is a feminine given name of Latin origin, commonly used in Spanish- and Italian-speaking cultures.
  • E. Rosalinda
    Rosalinda is a feminine given name of Spanish and Italian origin, often interpreted to mean "beautiful rose."
  • 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_69a8871289048190b00b0d7744b7b2b1 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb43011188190b6a41c004e9e4802 completed March 7, 2026, 5:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae032988ec8190b9012cbb77e7efa4 completed March 8, 2026, 11:15 p.m.
NEDg Description generation batch_69ae03c4faac8190a13aa0882eda3629 completed March 8, 2026, 11:18 p.m.
NED2 Entity disambiguation (via description) batch_69ae0445a9608190918a7bd45b9bf999 completed March 8, 2026, 11:20 p.m.
Created at: March 4, 2026, 7:36 p.m.