Triple
T33043528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Mosque of Banda Aceh |
E845532
|
entity |
| Predicate | damageFromEvent |
P150886
|
FINISHED |
| Object | minor damage in 2004 Indian Ocean 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: minor damage in 2004 Indian Ocean tsunami | Statement: [Great Mosque of Banda Aceh, damageFromEvent, minor damage in 2004 Indian Ocean tsunami]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: damageFromEvent Context triple: [Great Mosque of Banda Aceh, damageFromEvent, minor damage in 2004 Indian Ocean tsunami]
-
A.
damageOccurred
chosen
Indicates that some form of harm, loss, or deterioration has taken place as a result of an event or action.
-
B.
damageEffect
Indicates that one entity causes harm, reduction, or deterioration to another entity or its properties.
-
C.
damageLeadsTo
Indicates that one instance of damage causally results in or contributes to another specified outcome or condition.
-
D.
damageTo
Indicates a relationship where one entity causes harm, loss, or deterioration to another entity.
-
E.
damageBasis
Indicates the underlying reason, cause, or basis on which damage is determined or assessed in a given context.
- 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_69f3495242e48190996a2cb2beab5455 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d6a6b04c8190bee4cf9c00665ef7 |
completed | May 3, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69f6d27120988190aacec621cf2bf0e8 |
completed | May 3, 2026, 4:43 a.m. |
Created at: May 1, 2026, 1:24 a.m.