Triple
T20807839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Buccaneer (1938 film) |
E512210
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Jean Lafitte |
—
|
NE NERFINISHED |
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: Jean Lafitte | Statement: [The Buccaneer (1938 film), character, Jean Lafitte]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jean Lafitte Context triple: [The Buccaneer (1938 film), character, Jean Lafitte]
-
A.
Jean Lafitte
chosen
Jean Lafitte was a notorious early 19th-century French pirate and privateer in the Gulf of Mexico who became a folk-hero figure for aiding the United States during the War of 1812.
-
B.
Pierre Lafitte
Pierre Lafitte was a 19th-century privateer and smuggler who, alongside his more famous brother Jean Lafitte, operated in the Gulf of Mexico and around New Orleans.
-
C.
Chenier
Chenier is a French-origin surname borne by various notable individuals, including athletes, musicians, and public figures.
-
D.
Fermín Lafitte
Fermín Lafitte was a prominent Roman Catholic prelate who served as a leading archbishop in Buenos Aires, Argentina.
-
E.
Jean Dubois
Jean Dubois is a relatively common French personal name shared by multiple individuals across various fields, such as academia, politics, and the arts.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4cc69f481908e98751e697b9df4 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2d0a2a081908fb0e3d890e87aaf |
completed | April 21, 2026, 12:20 a.m. |
Created at: April 16, 2026, 12:40 p.m.