Triple
T20952351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francesco Rosi |
E516011
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Carmen
Carmen is Francesco Rosi’s 1984 film adaptation of Bizet’s famous opera, noted for its realistic setting and cinematic interpretation of the classic tragic love story.
|
E1460044
|
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: [Francesco Rosi, notableWork, Carmen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carmen Context triple: [Francesco Rosi, notableWork, Carmen]
-
A.
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.
-
B.
Carmen
Carmen is a landlocked agricultural municipality in the province of North Cotabato on the island of Mindanao in the Philippines.
-
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 character from the animated series "The Amazing World of Gumball," known as a strict, rule-abiding cactus who attends Elmore Junior High.
- 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: [Francesco Rosi, notableWork, Carmen]
Generated description
Carmen is Francesco Rosi’s 1984 film adaptation of Bizet’s famous opera, noted for its realistic setting and cinematic interpretation of the classic tragic love story.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Carmen Target entity description: Carmen is Francesco Rosi’s 1984 film adaptation of Bizet’s famous opera, noted for its realistic setting and cinematic interpretation of the classic tragic love story.
-
A.
Carmen
Carmen is a 1983 Spanish musical drama film directed by Carlos Saura that reimagines the classic Bizet opera through flamenco dance.
-
B.
Carmen
Carmen is a famous opera by Georges Bizet, renowned for its passionate music and tragic story centered on the free-spirited gypsy Carmen.
-
C.
Carmen
Carmen is a central character in the 2012 Spanish silent film "Blancanieves," a dark, flamenco-infused reimagining of the Snow White fairy tale.
-
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 character in the independent crime drama film "Dinner Rush," which centers on the high-pressure world of a New York City restaurant.
- 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_69e0b4fcd678819087a304291f14330a |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fadf85f88190924d3919b9e665e4 |
completed | April 21, 2026, 4:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09278fef048190bccac96353f891fd |
completed | May 17, 2026, 2:27 a.m. |
| NEDg | Description generation | batch_6a092b51f5648190bf446d4da1b16e7c |
completed | May 17, 2026, 2:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a092bf1b3b481908b5d9225ff36ad1b |
completed | May 17, 2026, 2:46 a.m. |
Created at: April 16, 2026, 1:27 p.m.