Triple
T15633479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1944 Tonankai earthquake |
E375877
|
entity |
| Predicate | tsunamiDamage |
P46843
|
FINISHED |
| Object | coastal flooding and destruction of fishing villages |
—
|
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: coastal flooding and destruction of fishing villages | Statement: [1944 Tonankai earthquake, tsunamiDamage, coastal flooding and destruction of fishing villages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tsunamiDamage Context triple: [1944 Tonankai earthquake, tsunamiDamage, coastal flooding and destruction of fishing villages]
-
A.
tsunamiAffectedArea
chosen
Indicates that a given area has been impacted or damaged by a tsunami.
-
B.
tsunamiGenerated
Indicates that a tsunami is produced or caused by a particular event or source.
-
C.
tsunamiType
Indicates the specific classification or category of a tsunami associated with an event or location.
-
D.
hasTsunamiRisk
Indicates that the subject is exposed to or associated with a potential risk of tsunamis.
-
E.
producedTsunami
Indicates that an event or phenomenon caused or generated a tsunami as a consequence.
- 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eb7338881909f3c430bb73f91d1 |
completed | April 16, 2026, 2:51 a.m. |
| PD | Predicate disambiguation | batch_69deda868d4481908f4bce1c64d2902a |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:14 a.m.