Triple
T19548849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jirau Dam |
E489144
|
entity |
| Predicate | hasConstructionImpact |
P136540
|
FINISHED |
| Object | deforestation in surrounding area |
—
|
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: deforestation in surrounding area | Statement: [Jirau Dam, hasConstructionImpact, deforestation in surrounding area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasConstructionImpact Context triple: [Jirau Dam, hasConstructionImpact, deforestation in surrounding area]
-
A.
hasConstruction
Indicates that one entity possesses, contains, or is characterized by a particular construction, structure, or built form associated with it.
-
B.
hasVisualImpact
Indicates that one entity affects or influences the visual appearance or aesthetic perception of another.
-
C.
canImpact
Indicates that one entity has the potential or ability to affect, influence, or cause a change in another entity.
-
D.
impactBuilding
Indicates that one entity physically collides with or strikes a building, causing an impact event.
-
E.
hasImpactScale
Indicates the degree or magnitude of impact that one entity or action has on another, typically expressed along a defined scale.
- 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63d2e5e588190ac3a6f612d4fb54b |
completed | April 20, 2026, 2:50 p.m. |
| PD | Predicate disambiguation | batch_69e514d4df3c8190b7e9b3b4fdf9452a |
completed | April 19, 2026, 5:45 p.m. |
| PDg | Predicate description generation | batch_69e51796b4c48190b721114dde654bd7 |
completed | April 19, 2026, 5:57 p.m. |
Created at: April 10, 2026, 1:41 p.m.