Triple
T26930060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bekasi River |
E678187
|
entity |
| Predicate | hasFloodRiskLevel |
P58564
|
FINISHED |
| Object | high in rainy season |
—
|
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: high in rainy season | Statement: [Bekasi River, hasFloodRiskLevel, high in rainy season]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFloodRiskLevel Context triple: [Bekasi River, hasFloodRiskLevel, high in rainy season]
-
A.
hasFloodRisk
Indicates that an entity is exposed to a potential or expected risk of flooding under certain conditions.
-
B.
hasFloodRiskRelevance
Indicates that something is pertinent to, affects, or is used in assessing the risk or likelihood of flooding.
-
C.
hasFloodRiskAreas
Indicates that certain areas are subject to potential flooding or are classified as being at risk of flood events.
-
D.
floodRiskCategory
chosen
Indicates the level or classification of flood risk associated with an entity, such as a location or asset.
-
E.
hasFloodplain
Indicates that an area or location lies within the floodplain associated with a particular water body or flooding source.
- 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_69eeeb4cac908190a45956c2993d1cc2 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f6562fd3488190be1acd8c526a28d2 |
completed | May 2, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69f651a931748190a637e631a52bbfaa |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 27, 2026, 6:12 a.m.