Triple
T440758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ahu Tongariki |
E10107
|
entity |
| Predicate | damageEvent |
P992
|
FINISHED |
| Object | 1960 Valdivia earthquake and tsunami |
—
|
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: 1960 Valdivia earthquake and tsunami | Statement: [Ahu Tongariki, damageEvent, 1960 Valdivia earthquake and tsunami]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: damageEvent Context triple: [Ahu Tongariki, damageEvent, 1960 Valdivia earthquake and tsunami]
-
A.
damagedBy
Indicates that one entity has caused harm, impairment, or deterioration to another entity.
-
B.
damagedIn
chosen
Indicates that an entity has suffered harm, impairment, or destruction as a result of a specified event, process, or condition.
-
C.
damageYear
Indicates the year in which the damage to an entity occurred or was recorded.
-
D.
fatalInjury
Indicates that an entity causes or sustains an injury that directly results in death.
-
E.
hasDam
Indicates that a watercourse, reservoir, or similar feature is impounded or controlled by a specific dam.
- 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_69a2e8465ef481909655c681b01e2986 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2ef2af84881909635ebbbb3465b1b |
completed | Feb. 28, 2026, 1:35 p.m. |
| PD | Predicate disambiguation | batch_69a2eddcf50c8190bfa0d1f8ee9f604a |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.