Triple
T25096346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2016 Kumamoto earthquakes |
E628599
|
entity |
| Predicate | mainAffectedTown |
P55202
|
FINISHED |
| Object | Mashiki |
—
|
NE NERFINISHED |
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: Mashiki | Statement: [2016 Kumamoto earthquakes, mainAffectedTown, Mashiki]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainAffectedTown Context triple: [2016 Kumamoto earthquakes, mainAffectedTown, Mashiki]
-
A.
affectedCity
Indicates that a particular city is impacted or influenced by a specified event, action, or condition.
-
B.
mainAffectedProvince
Indicates the province that is primarily impacted or influenced by a given event, action, or condition.
-
C.
worstAffectedVillage
Indicates that the village is the one most severely impacted or damaged in a given event or situation.
-
D.
involvedTown
chosen
Indicates that a town participates in, is associated with, or is affected by a particular event, activity, or relationship.
-
E.
primaryTown
Indicates that a given town is the main or most important town associated with an entity (such as a person, organization, or region).
- 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_69e2ff2f58e881908340527bc5d34f07 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f61f12b0f08190bc4a16907941864c |
completed | May 2, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69f61b37a5648190b10d33ae205ccfee |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 18, 2026, 6:25 a.m.