Triple
T36117937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japan Arc |
E1044660
|
entity |
| Predicate | hasHazardAssociationWith |
P138266
|
FINISHED |
| Object | tsunamis around Japan |
—
|
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: tsunamis around Japan | Statement: [Japan Arc, hasHazardAssociationWith, tsunamis around Japan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHazardAssociationWith Context triple: [Japan Arc, hasHazardAssociationWith, tsunamis around Japan]
-
A.
hasHazardRelation
chosen
Indicates a relationship where one entity poses, contributes to, or is associated with a potential hazard or risk affecting another entity.
-
B.
isHazardTo
Indicates that one entity poses a potential source of danger, harm, or risk to another entity.
-
C.
hasHazardCharacteristic
Indicates that an entity possesses a specific hazardous property, condition, or risk-related characteristic.
-
D.
isHazard
Indicates that something poses a potential risk, danger, or harmful condition to people, property, or the environment.
-
E.
hasNotableHazard
Indicates that an entity is associated with a significant risk, danger, or harmful condition that is noteworthy or exceptional.
- 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_69f76e344a4c8190af3858c6d78ba88f |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7ba6d06f48190a71b5a2f19e2232f |
completed | May 3, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a4aad48190a62e41c5e39339d9 |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:08 p.m.