Triple
T11457934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carib |
E271578
|
entity |
| Predicate | presentIn |
P795
|
FINISHED |
| Object | Grenada |
E14089
|
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: Grenada | Statement: [Carib, presentIn, Grenada]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grenada Context triple: [Carib, presentIn, Grenada]
-
A.
Grenada
chosen
Grenada is a small Caribbean island nation known for its spice production, picturesque beaches, and lush mountainous interior.
-
B.
Saint Vincent and the Grenadines
Saint Vincent and the Grenadines is a small Caribbean island nation known for its volcanic main island, numerous smaller Grenadine islands, and tourism centered on sailing and beaches.
-
C.
Dominica
Dominica is a small island nation in the Caribbean known for its lush rainforests, volcanic landscapes, and rich biodiversity.
-
D.
Saint Lucia
Saint Lucia is a small Caribbean island nation known for its dramatic Piton mountains, lush rainforests, and popular beach resorts.
-
E.
Barbados
Barbados is an island country in the Caribbean known for its beaches, coral reefs, and status as a popular tourist destination.
- 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_69d6aadff8888190a13f253f0d460874 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d81c71b1208190be1d5623d18e0222 |
completed | April 9, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e6040733648190a10f9553b3ac87a7 |
completed | April 20, 2026, 10:46 a.m. |
Created at: April 8, 2026, 9:35 p.m.