Triple
T35385203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanauan, Leyte |
E1022770
|
entity |
| Predicate | isDisasterProneArea |
P44599
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Tanauan, Leyte, isDisasterProneArea, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isDisasterProneArea Context triple: [Tanauan, Leyte, isDisasterProneArea, true]
-
A.
hasNaturalHazardRisk
chosen
Indicates that an entity is exposed or subject to potential damage or impact from one or more natural hazards (e.g., earthquakes, floods, storms).
-
B.
geologicalHazardZoneFor
Indicates a relationship where a specified area or zone is identified as being at risk from a particular geological hazard (such as earthquakes, landslides, or volcanic activity).
-
C.
disasterLocation
Indicates the place where a disaster occurs or has its primary impact.
-
D.
hasCoastalRisk
Indicates that an entity is exposed to potential hazards or adverse impacts associated with coastal environments, such as flooding, erosion, or storm surge.
-
E.
hasAvalancheRisk
Indicates that there is a potential or assessed danger of an avalanche occurring in relation to the referenced entity.
- 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_69f76df28d8c819089f2c5799fe7d079 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f794f50080819095ff3c2cefc74fea |
completed | May 3, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69f7910770108190bdd39ddb5d304f54 |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.