Triple
T33195585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mullaperiyar Dam |
E849747
|
entity |
| Predicate | downstreamRiskArea |
P176172
|
FINISHED |
| Object | Idukki Reservoir |
—
|
NE NERFINISHED |
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: Idukki Reservoir | Statement: [Mullaperiyar Dam, downstreamRiskArea, Idukki Reservoir]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: downstreamRiskArea Context triple: [Mullaperiyar Dam, downstreamRiskArea, Idukki Reservoir]
-
A.
hasRiskFrom
Indicates that one entity is exposed to or may suffer potential harm, loss, or adverse effects as a result of another entity.
-
B.
riskDomain
Indicates that something belongs to, is associated with, or falls under a particular area or category of risk.
-
C.
riskZone
Indicates that an entity is located within or associated with an area characterized by elevated danger, threat, or potential harm.
-
D.
riskElement
Indicates that one entity is a risk-related component, factor, or contributor associated with another entity within a risk context.
-
E.
riskReductionFor
Indicates a relationship where one entity decreases or mitigates the level of risk associated with another entity or situation.
- F. None of above. chosen
Provenance (4 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_69f3495efedc8190843a5728089544b9 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6dd3cc0648190a275812d6711275a |
completed | May 3, 2026, 5:29 a.m. |
| PD | Predicate disambiguation | batch_69f6d82eaee081908f06a71546315aea |
completed | May 3, 2026, 5:07 a.m. |
| PDg | Predicate description generation | batch_69f6dd3b335481909e24d4eb5b0269f9 |
completed | May 3, 2026, 5:29 a.m. |
Created at: May 1, 2026, 1:29 a.m.