Triple

T5633392
Position Surface form Disambiguated ID Type / Status
Subject Carlos Saura E147886 entity
Predicate notableWork P4 FINISHED
Object Carmen
Carmen is a 1983 Spanish musical drama film directed by Carlos Saura that reimagines the classic Bizet opera through flamenco dance.
E540940 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: Carmen | Statement: [Carlos Saura, notableWork, Carmen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carmen
Context triple: [Carlos Saura, notableWork, Carmen]
  • A. Carmen
    Carmen is a key character in the dark fantasy film "Pan’s Labyrinth," serving as the pregnant mother whose fragile health and marriage to a brutal captain frame the story’s wartime and familial tensions.
  • B. Carmen
    Carmen is a central district of San José, Costa Rica, known for its urban character and role in the capital’s administrative and commercial life.
  • C. Carmen
    Carmen is a supporting character in Jim Jarmusch’s film "Broken Flowers," connected to the protagonist’s journey to revisit women from his past.
  • D. Carmen
    Carmen is a landlocked municipality in the central part of Bohol Island in the Philippines, known for its proximity to the famous Chocolate Hills.
  • E. Carmen
    Carmen is a pivotal character in the 1986 film "The Color of Money," serving as the savvy and manipulative girlfriend-manager of young pool hustler Vincent Lauria.
  • 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: Carmen
Triple: [Carlos Saura, notableWork, Carmen]
Generated description
Carmen is a 1983 Spanish musical drama film directed by Carlos Saura that reimagines the classic Bizet opera through flamenco dance.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Carmen
Target entity description: Carmen is a 1983 Spanish musical drama film directed by Carlos Saura that reimagines the classic Bizet opera through flamenco dance.
  • A. Carmen
    Carmen is a famous opera by Georges Bizet, renowned for its passionate music and tragic story centered on the free-spirited gypsy Carmen.
  • B. Carmen
    Carmen is a pivotal character in the 1986 film "The Color of Money," serving as the savvy and manipulative girlfriend-manager of young pool hustler Vincent Lauria.
  • C. Carmen
    Carmen is a feminine given name of Latin origin, widely used in Spanish-speaking cultures and beyond.
  • D. Carmen
    Carmen is a key character in the dark fantasy film "Pan’s Labyrinth," serving as the pregnant mother whose fragile health and marriage to a brutal captain frame the story’s wartime and familial tensions.
  • E. Carmen
    Carmen is a supporting character in Jim Jarmusch’s film "Broken Flowers," connected to the protagonist’s journey to revisit women from his past.
  • 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_69c00907bc8881909ed760d3ed73ef35 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c0225ff3248190b93c9f5887553fd4 completed March 22, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a1666d88190af4c1890247f897d completed March 22, 2026, 9:07 p.m.
NEDg Description generation batch_69c05c471c3081909e5bf44f47388a7c completed March 22, 2026, 9:16 p.m.
NED2 Entity disambiguation (via description) batch_69c05cda809c81908219947cf06c381a completed March 22, 2026, 9:19 p.m.
Created at: March 22, 2026, 3:41 p.m.