Triple
T1443049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Préféte Duffaut |
E31116
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Préféte Duffaut |
E31116
|
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: Préféte Duffaut | Statement: [Préféte Duffaut, name, Préféte Duffaut]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Préféte Duffaut Context triple: [Préféte Duffaut, name, Préféte Duffaut]
-
A.
Préféte Duffaut
chosen
Préféte Duffaut was a renowned Haitian painter celebrated for his imaginative, dreamlike cityscapes and significant contributions to Haitian naïve art.
-
B.
Bézu Fache
Bézu Fache is the stern and devout captain of the French Judicial Police who leads the investigation at the Louvre in Dan Brown’s novel *The Da Vinci Code*.
-
C.
Ganthier
Ganthier is a commune in western Haiti known for its rural character and proximity to the capital, Port-au-Prince.
-
D.
De La Motte
De La Motte is a French-origin surname historically associated with various notable figures, including early 20th-century American silent film actress Marguerite De La Motte.
-
E.
Giraud
Giraud is a French surname borne by various notable figures in French history and culture.
- 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_69a4991633388190a4d61b5a98aa407a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c533a158819084d0917776edb6e5 |
completed | March 1, 2026, 11:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad08be450c8190bc0b8a69733a0bd4 |
completed | March 8, 2026, 5:27 a.m. |
Created at: March 1, 2026, 8 p.m.