Triple
T12067031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Lucia Carnival |
E287322
|
entity |
| Predicate | hasActivity |
P81
|
FINISHED |
| Object | Jouvert |
E554340
|
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: Jouvert | Statement: [St. Lucia Carnival, hasActivity, Jouvert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jouvert Context triple: [St. Lucia Carnival, hasActivity, Jouvert]
-
A.
Jouvert
chosen
Jouvert is a pre-dawn street celebration in Trinidad marked by music, dancing, and revelers covered in paint, mud, or oil to launch the Carnival festivities.
-
B.
Port-Marly
Port-Marly is a small riverside commune in north-central France, known for its picturesque setting along the Seine and its association with Impressionist painters.
-
C.
Port-de-Paix, Haiti
Port-de-Paix is a coastal city in northwestern Haiti known historically as a colonial port and regional commercial center on the Caribbean Sea.
-
D.
Abataranika
Abataranika is a Bengali literary work that served as the source material for the film "Mahanagar."
-
E.
Bonbon Beach
Bonbon Beach is a picturesque white-sand beach in Romblon, Philippines, known for its clear turquoise waters and a scenic sandbar that appears at low tide.
- 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_69d6ab4846e081908ee7bbd66a6d3459 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d904423dc08190a47194422255c62e |
completed | April 10, 2026, 2:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f658bb38819097547d392fcc5405 |
completed | May 2, 2026, 1:04 p.m. |
Created at: April 8, 2026, 9:48 p.m.