Triple
T36698592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | pueblo Siona |
E906156
|
entity |
| Predicate | amenazas |
P147428
|
FINISHED |
| Object | deforestación amazónica |
—
|
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: deforestación amazónica | Statement: [pueblo Siona, amenazas, deforestación amazónica]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: amenazas Context triple: [pueblo Siona, amenazas, deforestación amazónica]
-
A.
threatsFaced
chosen
Indicates that an entity is exposed to or experiences specific dangers, risks, or harmful conditions.
-
B.
threatenedBy
Indicates that one entity poses a danger or potential harm to another entity.
-
C.
threatToHumans
Indicates that the subject poses or represents a potential danger, harm, or risk to humans.
-
D.
hasThreats
Indicates that one entity poses or is associated with potential danger, harm, or adverse consequences toward another entity.
-
E.
threatenedUseOf
Indicates a situation where one entity has expressed or implied an intention to use force, harm, or coercive action against another entity.
- F. None of above.
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_69f76e7195c48190b5580c9cfb01e95f |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c7ebdea48190b0e7565e4e09ec9e |
completed | May 3, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69f7c4796ebc819084a0dc08505e5f14 |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:12 p.m.