Triple
T36627661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tarragona, Davao Oriental |
E904219
|
entity |
| Predicate | hasTropicalCycloneExposure |
P76970
|
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: [Tarragona, Davao Oriental, hasTropicalCycloneExposure, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTropicalCycloneExposure Context triple: [Tarragona, Davao Oriental, hasTropicalCycloneExposure, true]
-
A.
hasTropicalCyclones
chosen
Indicates that the specified region or area experiences tropical cyclones as part of its typical weather or climate conditions.
-
B.
hasLandfallOf
Indicates that a storm or weather system makes landfall at or affects a particular geographic location.
-
C.
hasCoastalRisk
Indicates that an entity is exposed to potential hazards or adverse impacts associated with coastal environments, such as flooding, erosion, or storm surge.
-
D.
hasTsunamiRisk
Indicates that the subject is exposed to or associated with a potential risk of tsunamis.
-
E.
isTropicalCycloneBasin
Indicates that a given geographic region or body of water functions as a basin where tropical cyclones can form or occur.
- 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_69f76e6ae750819096911e6e2d4d12c5 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fffc783b648190bcd7df017514d206 |
completed | May 10, 2026, 3:33 a.m. |
| PD | Predicate disambiguation | batch_69fffc03fa24819099e12413dc6e0afd |
completed | May 10, 2026, 3:31 a.m. |
Created at: May 3, 2026, 4:11 p.m.