Triple
T17202279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bamban |
E417504
|
entity |
| Predicate | hasPostDisasterRole |
P103649
|
FINISHED |
| Object | center for resettlement and rehabilitation after Mount Pinatubo eruption |
—
|
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: center for resettlement and rehabilitation after Mount Pinatubo eruption | Statement: [Bamban, hasPostDisasterRole, center for resettlement and rehabilitation after Mount Pinatubo eruption]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPostDisasterRole Context triple: [Bamban, hasPostDisasterRole, center for resettlement and rehabilitation after Mount Pinatubo eruption]
-
A.
postDisasterRole
chosen
Indicates the role or function an entity assumes or performs in the aftermath of a disaster.
-
B.
hasDisaster
Indicates that an entity experiences, is affected by, or is associated with a disaster event.
-
C.
hasDisasterElement
Indicates that something includes, involves, or is characterized by an element or aspect of a disaster.
-
D.
roleInDisasterMovie
Indicates that an entity has a specific acting or production role in a disaster-themed movie.
-
E.
supportsDisasterType
Indicates that one entity is capable of handling, responding to, or being applicable to a specified type of disaster.
- 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_69d886d6ba8c819093215917b3d01689 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42db014b08190b88a5001e9f7811b |
completed | April 19, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69e3831e354881908c5505ffd15c84e9 |
completed | April 18, 2026, 1:11 p.m. |
Created at: April 10, 2026, 5:38 a.m.