Triple
T2375853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastern Visayas |
E46196
|
entity |
| Predicate | disasterRisk |
P24786
|
FINISHED |
| Object | high exposure to storm surges |
—
|
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: high exposure to storm surges | Statement: [Eastern Visayas, disasterRisk, high exposure to storm surges]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: disasterRisk Context triple: [Eastern Visayas, disasterRisk, high exposure to storm surges]
-
A.
frequentNaturalHazard
Indicates that a location or area regularly experiences natural hazards such as floods, earthquakes, storms, or similar events with notable frequency.
-
B.
hasDisaster
Indicates that an entity experiences, is affected by, or is associated with a disaster event.
-
C.
hasTsunamiRisk
chosen
Indicates that the subject is exposed to or associated with a potential risk of tsunamis.
-
D.
earthquakeHazardLevel
Indicates the assessed degree of risk or potential impact from earthquakes associated with a given location or entity.
-
E.
humanitarianCrisis
Indicates a situation in which a population faces severe, widespread threats to life, health, or basic living conditions that require urgent humanitarian assistance.
- 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_69a88a1554a48190a0180682bcf099be |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abca4d89248190be7d712d5fa8382b |
completed | March 7, 2026, 6:48 a.m. |
| PD | Predicate disambiguation | batch_69abc59d82f08190b7c36982d1ae783d |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:57 p.m.