Triple

T18958273
Position Surface form Disambiguated ID Type / Status
Subject Rise Stevens E463838 entity
Predicate notableWork P4 FINISHED
Object Carmen
Carmen is a famous opera by Georges Bizet, renowned for its passionate story, memorable melodies, and the iconic role of the seductive gypsy Carmen.
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: [Rise Stevens, notableWork, Carmen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carmen
Context triple: [Rise Stevens, 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 landlocked municipality in the central part of Bohol Island in the Philippines, known for its proximity to the famous Chocolate Hills.
  • C. 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.
  • D. 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.
  • E. 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.
  • 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: [Rise Stevens, notableWork, Carmen]
Generated description
Carmen is a famous opera by Georges Bizet, renowned for its passionate story, memorable melodies, and the iconic role of the seductive gypsy Carmen.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Carmen
Target entity description: Carmen is a famous opera by Georges Bizet, renowned for its passionate story, memorable melodies, and the iconic role of the seductive gypsy Carmen.
  • 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 central character in the 2012 Spanish silent film "Blancanieves," a dark, flamenco-infused reimagining of the Snow White fairy tale.
  • E. Carmen
    Carmen is the central protagonist of the story "Abracadabra," around whom the plot and character dynamics revolve.
  • 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_69d8dcffc278819086792a4ebfddfafa completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d5d057a48190b82b5788b3281e28 completed April 20, 2026, 7:29 a.m.
NED1 Entity disambiguation (via context triple) batch_6a059fd732f8819087374b0157bb693e completed May 14, 2026, 10:11 a.m.
NEDg Description generation batch_6a05a161c8e88190a6f9c9abe3314487 completed May 14, 2026, 10:18 a.m.
NED2 Entity disambiguation (via description) batch_6a05a1cb500481908608daee7537dd0c completed May 14, 2026, 10:19 a.m.
Created at: April 10, 2026, noon