Triple
T32585055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sierra Maestra forests |
E832897
|
entity |
| Predicate | ecoregionName |
P174624
|
FINISHED |
| Object | Cuban moist forests |
—
|
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: Cuban moist forests | Statement: [Sierra Maestra forests, ecoregionName, Cuban moist forests]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ecoregionName Context triple: [Sierra Maestra forests, ecoregionName, Cuban moist forests]
-
A.
ecoregion
Indicates that one entity is located within, associated with, or belongs to the same ecological region as another entity.
-
B.
ecoregionCode
Indicates the specific ecological region identifier associated with an entity, linking it to a defined environmental or biogeographic zone.
-
C.
ecoregionContext
Indicates the environmental or ecological setting within which an entity exists or an interaction occurs, defined by its surrounding ecoregion.
-
D.
ecoregionsInclude
Indicates that one ecoregion spatially contains or encompasses another ecoregion or area within its boundaries.
-
E.
ecozone
Indicates that two entities stand in a biogeographical relationship where one is an ecological zone (ecozone) that characterizes or contains the other.
- 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_69f349289adc81909f4374a58ec35a39 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c66d08708190809cadede7084f54 |
completed | May 3, 2026, 3:52 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2c138481908afa3ee3e91f8900 |
completed | May 3, 2026, 3:12 a.m. |
| PDg | Predicate description generation | batch_69f6c2df27ec8190912ec8eb488836d0 |
completed | May 3, 2026, 3:37 a.m. |
Created at: May 1, 2026, 1:04 a.m.