Triple
T5704077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jalisco Block |
E125739
|
entity |
| Predicate | hasHazardRelevance |
P30182
|
FINISHED |
| Object | tsunami potential from subduction earthquakes |
—
|
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: tsunami potential from subduction earthquakes | Statement: [Jalisco Block, hasHazardRelevance, tsunami potential from subduction earthquakes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHazardRelevance Context triple: [Jalisco Block, hasHazardRelevance, tsunami potential from subduction earthquakes]
-
A.
hasHazardLevel
Indicates that an entity is associated with a specified degree or category of risk or danger.
-
B.
hasNavigationHazardRelevance
Indicates that something is relevant to, affected by, or poses a potential hazard to navigation.
-
C.
hasNotableHazard
Indicates that an entity is associated with a significant risk, danger, or harmful condition that is noteworthy or exceptional.
-
D.
safetyRelevant
chosen
Indicates that the associated entity, condition, or information has a direct impact on safety or is critical for preventing harm or accidents.
-
E.
hasObjectiveHazards
Indicates that an entity is associated with concrete, externally verifiable dangers or risks.
- 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_69c0082c96988190b3a6a201edce472a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c024585d14819098ec34fd5a858836 |
completed | March 22, 2026, 5:18 p.m. |
| PD | Predicate disambiguation | batch_69c021c2d8bc8190b947c7d1f423d2f3 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:45 p.m.