Triple
T8107677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don José |
E189266
|
entity |
| Predicate | basedOn |
P98
|
FINISHED |
| Object | Don José from Prosper Mérimée’s novella Carmen |
E189266
|
NE FINISHED |
How this triple was built (2 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: Don José from Prosper Mérimée’s novella Carmen | Statement: [Don José, basedOn, Don José from Prosper Mérimée’s novella Carmen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Don José from Prosper Mérimée’s novella Carmen Context triple: [Don José, basedOn, Don José from Prosper Mérimée’s novella Carmen]
-
A.
Don José
chosen
Don José is the tragic soldier protagonist of Georges Bizet’s opera "Carmen," whose obsessive love for the title character leads to his downfall.
-
B.
Joaquín Toesca
Joaquín Toesca was an 18th-century Italian-born architect who became a key figure in Chilean neoclassical architecture.
-
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 district of San José, Costa Rica, known for its urban character and role in the capital’s administrative and commercial life.
-
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.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca82b9d5848190a24672775d5c5011 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb42fa40e08190955fccec1a28eb34 |
completed | March 31, 2026, 3:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc94198fdc8190bcf3c6285e52fdd3 |
completed | April 1, 2026, 3:42 a.m. |
Created at: March 30, 2026, 5:32 p.m.