Triple
T26274350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sandy Brook |
E660517
|
entity |
| Predicate | hasPotentialRisk |
P136373
|
FINISHED |
| Object | vulnerable to pollution from surrounding land use |
—
|
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: vulnerable to pollution from surrounding land use | Statement: [Sandy Brook, hasPotentialRisk, vulnerable to pollution from surrounding land use]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPotentialRisk Context triple: [Sandy Brook, hasPotentialRisk, vulnerable to pollution from surrounding land use]
-
A.
hasRiskFrom
chosen
Indicates that one entity is exposed to or may suffer potential harm, loss, or adverse effects as a result of another entity.
-
B.
hasRiskStatus
Indicates the level or category of risk currently associated with an entity.
-
C.
hasRiskFactorFor
Indicates that one entity contributes to or increases the likelihood of another entity experiencing a particular risk or adverse outcome.
-
D.
hasPotential
Indicates that an entity possesses the capacity or possibility to develop, achieve, or exhibit a particular state, quality, or outcome in the future.
-
E.
hasPregnancyRisk
Indicates that one entity poses or is associated with a potential risk of causing pregnancy for 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_69ee812960d081909cff6085cc9fa3a6 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f6df450014819099d118e5c2d697fa |
completed | May 3, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69f6de07836481908785cde9c511920b |
completed | May 3, 2026, 5:32 a.m. |
Created at: April 26, 2026, 9:54 p.m.