Triple
T28840313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sidoarjo mudflow |
E728294
|
entity |
| Predicate | impactOnSettlements |
P124172
|
FINISHED |
| Object | destruction of homes |
—
|
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: destruction of homes | Statement: [Sidoarjo mudflow, impactOnSettlements, destruction of homes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnSettlements Context triple: [Sidoarjo mudflow, impactOnSettlements, destruction of homes]
-
A.
influencesSettlement
Indicates that one entity affects or shapes the establishment, development, or characteristics of a settlement.
-
B.
settlementEffect
Indicates the impact or consequences that a particular settlement (such as a legal, financial, or dispute resolution agreement) has on the involved parties or situation.
-
C.
numberOfAffectedSettlements
Indicates the count of distinct settlements that are impacted by a particular event, condition, or action.
-
D.
impactOnStates
Indicates the effect or influence that one entity, event, or condition has on the status, condition, or behavior of one or more states.
-
E.
impactOfDisasters
chosen
Indicates the effects or consequences that disasters have on entities, conditions, or outcomes.
- 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_69f0319e8e7c8190b37288c8845b9dbc |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f6d6a6b04c8190bee4cf9c00665ef7 |
completed | May 3, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69f6d26ceb08819091c71c001e954936 |
completed | May 3, 2026, 4:43 a.m. |
Created at: April 28, 2026, 6:40 a.m.