Triple
T1360045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hispaniola |
E29077
|
entity |
| Predicate | rankByAreaInCaribbean |
P27430
|
FINISHED |
| Object | second-largest island in the Caribbean |
—
|
LITERAL 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: second-largest island in the Caribbean | Statement: [Hispaniola, rankByAreaInCaribbean, second-largest island in the Caribbean]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankByAreaInCaribbean Context triple: [Hispaniola, rankByAreaInCaribbean, second-largest island in the Caribbean]
-
A.
rankInWorldByArea
Indicates the position of an entity in a global ordering based on its total area size.
-
B.
rankInBritishIslesByArea
Indicates the position of an entity in an ordered list of areas specifically within the British Isles, based on its size relative to others.
-
C.
locatedInCaribbean
Indicates that one entity is geographically situated within the Caribbean region.
-
D.
continentRankByArea
Indicates the relative position of a continent in an ordered list based on its total land area.
-
E.
landArea
Indicates the total surface area of a piece of land associated with an entity, typically measured in standardized units (e.g., square meters, hectares).
- F. None of above. chosen
Provenance (4 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_69a498d77abc8190913bf57e5f51d2c4 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c2b156b081909c99ada70a969fc0 |
completed | March 1, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69a4bef945c08190a027472fdd695ea5 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c06721488190ac7f6e012f21af3d |
completed | March 1, 2026, 10:40 p.m. |
Created at: March 1, 2026, 7:56 p.m.