Triple
T20299740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matsigenka |
E505445
|
entity |
| Predicate | facesThreatsFrom |
P43422
|
FINISHED |
| Object | oil and gas development |
—
|
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: oil and gas development | Statement: [Matsigenka, facesThreatsFrom, oil and gas development]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: facesThreatsFrom Context triple: [Matsigenka, facesThreatsFrom, oil and gas development]
-
A.
facesThreat
chosen
Indicates that an entity is exposed to or confronted by a potential danger, risk, or harmful situation.
-
B.
hasThreats
Indicates that one entity poses or is associated with potential danger, harm, or adverse consequences toward another entity.
-
C.
targetsThreat
Indicates that one entity is directing an action or focus specifically toward a perceived threat.
-
D.
laterThreat
Indicates that one entity poses a threat to another at a time subsequent to some referenced or initial point.
-
E.
threatToHumans
Indicates that the subject poses or represents a potential danger, harm, or risk to humans.
- 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_69e0b4b8ab648190906e18538c250148 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6770b9484819090ffcb339f2a435a |
completed | April 20, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69e55b21b09081909e46691b6f45a07f |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 16, 2026, 11:16 a.m.