Triple
T7654295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hualālai |
E173336
|
entity |
| Predicate | posesHazardTo |
P23477
|
FINISHED |
| Object | Kona coast communities |
—
|
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: Kona coast communities | Statement: [Hualālai, posesHazardTo, Kona coast communities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: posesHazardTo Context triple: [Hualālai, posesHazardTo, Kona coast communities]
-
A.
hazardType
Indicates the specific kind or category of hazard associated with an entity or situation.
-
B.
hasNotableHazard
Indicates that an entity is associated with a significant risk, danger, or harmful condition that is noteworthy or exceptional.
-
C.
hasObjectiveHazards
Indicates that an entity is associated with concrete, externally verifiable dangers or risks.
-
D.
dangerousWhen
Indicates that one entity becomes harmful, risky, or unsafe under the conditions or in the presence of another entity or situation.
-
E.
hazardScope
chosen
Indicates the range or extent within which a particular hazard is relevant, applicable, or has effect.
- 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_69c6995473348190a4f41d110d619a18 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7061cbc3c8190a917dd7e71214182 |
completed | March 27, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69c7015dd8fc8190bc5f52a12bd46209 |
completed | March 27, 2026, 10:14 p.m. |
Created at: March 27, 2026, 3:59 p.m.