Triple
T16832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North America |
E335
|
entity |
| Predicate | hasCountry |
P846
|
FINISHED |
| Object | Haiti |
E4291
|
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: Haiti | Statement: [North America, hasCountry, Haiti]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haiti Context triple: [North America, hasCountry, Haiti]
-
A.
Haiti
chosen
Haiti is a Caribbean nation on the island of Hispaniola known for its rich Afro-Caribbean culture, history as the first independent Black republic, and frequent vulnerability to natural disasters.
-
B.
Grenada
Grenada is a small Caribbean island nation known for its spice production, picturesque beaches, and lush mountainous interior.
-
C.
Dominica
Dominica is a small island nation in the Caribbean known for its lush rainforests, volcanic landscapes, and rich biodiversity.
-
D.
Cuba
Cuba is a Caribbean island nation known for its communist government, historic Havana architecture, classic cars, and influential music and culture.
-
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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a2465c52d8819082bb02b8b539d6ab |
completed | Feb. 28, 2026, 1:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2c26f0f208190b407df744062d1f0 |
completed | Feb. 28, 2026, 10:24 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.