Triple
T1171069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agent Orange |
E24912
|
entity |
| Predicate | effectOnEnvironment |
P5628
|
FINISHED |
| Object | deforestation |
—
|
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 | Statement: [Agent Orange, effectOnEnvironment, deforestation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnEnvironment Context triple: [Agent Orange, effectOnEnvironment, deforestation]
-
A.
hasEnvironmentalImpactOn
chosen
Indicates that one entity affects or alters the environmental conditions, quality, or ecological state of another entity.
-
B.
humanImpact
Indicates the effect or influence that human activities have on another entity, system, or environment.
-
C.
environmentalSignificance
Indicates the importance or impact that something has on the natural environment, such as its role in conservation, degradation, or ecological balance.
-
D.
environmentalIssue
Indicates that something is a problem or concern related to the natural environment, such as harm, risk, or negative impact on ecosystems or resources.
-
E.
environmentalFocus
Indicates a relationship where an entity prioritizes or concentrates on environmental issues, impacts, or sustainability in its actions or policies.
- 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_69a494082a7c819095004f423f294a64 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bce972cc8190bce0b77cfda6da41 |
completed | March 1, 2026, 10:25 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5656948190b0b1d5446ad06005 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:45 p.m.