Triple
T6564414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sorrow of Bihar |
E153865
|
entity |
| Predicate | naturalHazardType |
P1950
|
FINISHED |
| Object | riverine flooding |
—
|
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: riverine flooding | Statement: [Sorrow of Bihar, naturalHazardType, riverine flooding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: naturalHazardType Context triple: [Sorrow of Bihar, naturalHazardType, riverine flooding]
-
A.
frequentNaturalHazard
Indicates that a location or area regularly experiences natural hazards such as floods, earthquakes, storms, or similar events with notable frequency.
-
B.
notableDisasterType
Indicates the specific kind or category of disaster for which something (such as a place, event, or entity) is notable or best known.
-
C.
hasNaturalHazardRisk
Indicates that an entity is exposed or subject to potential damage or impact from one or more natural hazards (e.g., earthquakes, floods, storms).
-
D.
hasNaturalPhenomenon
Indicates that a location, region, or environment possesses or is characterized by a particular natural phenomenon (such as a weather event, geological feature, or celestial occurrence).
-
E.
hazardType
chosen
Indicates the specific kind or category of hazard associated with an entity or situation.
- 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_69c6880cb35881909b763eb0125236b9 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6cc9c6cb0819084fec8e0beb430de |
completed | March 27, 2026, 6:29 p.m. |
| PD | Predicate disambiguation | batch_69c6acf93cb48190b54f5dd6febd34dc |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:52 p.m.