Triple
T24091185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ava-Canoeiro |
E596788
|
entity |
| Predicate | impactOfContact |
P54758
|
FINISHED |
| Object | severe threat to traditional way of life |
—
|
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: severe threat to traditional way of life | Statement: [Ava-Canoeiro, impactOfContact, severe threat to traditional way of life]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOfContact Context triple: [Ava-Canoeiro, impactOfContact, severe threat to traditional way of life]
-
A.
impactStatus
Indicates the current state or condition of how something has affected or influenced a target.
-
B.
impactOutcome
chosen
Indicates that one entity produces an effect or influence that changes the result, consequence, or final state of another entity or situation.
-
C.
impactOnField
Indicates the effect or influence that one entity, action, or development has on a particular field or domain.
-
D.
impactOrigin
Indicates that one entity is the source or cause from which the impact or effect on another entity originates.
-
E.
collision
Indicates that two or more entities come into contact with each other at the same place and time, typically involving an impact or crash.
- 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_69e288c4638c81909bacc28a1e3d436b |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1dc2e672c8190b3e4be041835cc27 |
completed | April 29, 2026, 10:23 a.m. |
| PD | Predicate disambiguation | batch_69f17651458c8190bbfd301883e46085 |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 10:53 p.m.