Triple

T12775365
Position Surface form Disambiguated ID Type / Status
Subject Henri Meilhac E305354 entity
Predicate wroteLibrettoFor P1360 FINISHED
Object Carmen
Carmen is a famous 1875 French opera by Georges Bizet, renowned for its passionate music and tragic story set in Spain.
E36362 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: [Henri Meilhac, wroteLibrettoFor, Carmen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carmen
Context triple: [Henri Meilhac, wroteLibrettoFor, 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 key character in the 2012 ensemble comedy-drama film "Darling Companion," which centers on family relationships and the search for a lost dog.
  • E. Carmen
    Carmen is a 1983 Spanish musical drama film directed by Carlos Saura that reimagines the classic Bizet opera through flamenco dance.
  • 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: [Henri Meilhac, wroteLibrettoFor, Carmen]
Generated description
Carmen is a famous 1875 French opera by Georges Bizet, renowned for its passionate music and tragic story set in Spain.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Carmen
Target entity description: Carmen is a famous 1875 French opera by Georges Bizet, renowned for its passionate music and tragic story set in Spain.
  • A. Carmen chosen
    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 1983 Spanish musical drama film directed by Carlos Saura that reimagines the classic Bizet opera through flamenco dance.
  • C. Carmen
    Carmen is a feminine given name of Latin origin, widely used in Spanish-speaking cultures and beyond.
  • 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 municipality in the province of Cebu in the Philippines, known for its agricultural economy and proximity to coastal and upland attractions.
  • F. None of above.

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_69d7bdf2b43c819098ae5aa68e61ea58 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96df6b3c88190b0bbe70de8ddcbf3 completed April 10, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68eba76008190ad9df2e2a5423471 completed May 2, 2026, 11:54 p.m.
NEDg Description generation batch_69f6916dfb2c819098c087b02c07618f completed May 3, 2026, 12:06 a.m.
NED2 Entity disambiguation (via description) batch_69f692017adc8190a07ab274958c7b0a completed May 3, 2026, 12:08 a.m.
Created at: April 9, 2026, 5:29 p.m.