Triple
T17771463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Nicolas, Batangas |
E443648
|
entity |
| Predicate | hasHazardExposure |
P63246
|
FINISHED |
| Object | volcanic eruptions |
—
|
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: volcanic eruptions | Statement: [San Nicolas, Batangas, hasHazardExposure, volcanic eruptions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHazardExposure Context triple: [San Nicolas, Batangas, hasHazardExposure, volcanic eruptions]
-
A.
hasHazardLevel
Indicates that an entity is associated with a specified degree or category of risk or danger.
-
B.
hasNotableHazard
Indicates that an entity is associated with a significant risk, danger, or harmful condition that is noteworthy or exceptional.
-
C.
hasObjectiveHazards
chosen
Indicates that an entity is associated with concrete, externally verifiable dangers or risks.
-
D.
hasEnvironmentalRisk
Indicates that an entity poses, contributes to, or is associated with potential harm or adverse impact on the environment.
-
E.
locatedNearHazard
Indicates that one entity is situated in close physical proximity to a hazardous object, area, or condition.
- 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_69d8b9ef17708190bdf7e2adbf14ddc2 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e486005770819085d637279b2334eb |
completed | April 19, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69e3d8d8e538819084f1584426b41d5e |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:11 a.m.