Triple
T47714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haitian Creole |
E937
|
entity |
| Predicate | spokenIn |
P2266
|
FINISHED |
| Object | Martinique |
E26301
|
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: Martinique | Statement: [Haitian Creole, spokenIn, Martinique]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Martinique Context triple: [Haitian Creole, spokenIn, Martinique]
-
A.
Martinique
chosen
Martinique is a Caribbean island and French overseas region known for its blend of French and Creole culture, volcanic landscapes, and beaches.
-
B.
Guadeloupe
Guadeloupe is a Caribbean archipelago that forms an overseas region and department of France, known for its blend of French and Creole culture, volcanic landscapes, and beaches.
-
C.
Réunion
Réunion is a French island and overseas department in the Indian Ocean known for its volcanic landscapes, multicultural population, and status as an outermost region of the European Union.
-
D.
Dominica
Dominica is a small island nation in the Caribbean known for its lush rainforests, volcanic landscapes, and rich biodiversity.
-
E.
Saint Lucia
Saint Lucia is a small Caribbean island nation known for its dramatic Piton mountains, lush rainforests, and popular beach resorts.
- 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_69a2480baefc81909951b14058479aa2 |
completed | Feb. 28, 2026, 1:42 a.m. |
| NER | Named-entity recognition | batch_69a24ec333fc8190b66776b947e0bdbd |
completed | Feb. 28, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a34d8edb8c81909c7229fe6e4c0569 |
completed | Feb. 28, 2026, 8:18 p.m. |
Created at: Feb. 28, 2026, 1:47 a.m.