Triple
T1729124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bhima River |
E37568
|
entity |
| Predicate | floodProne |
P12640
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Bhima River, floodProne, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: floodProne Context triple: [Bhima River, floodProne, yes]
-
A.
hasFloodplain
Indicates that an area or location lies within the floodplain associated with a particular water body or flooding source.
-
B.
hasFloodRisk
chosen
Indicates that an entity is exposed to a potential or expected risk of flooding under certain conditions.
-
C.
hasSeasonalFlooding
Indicates that an area regularly experiences flooding during specific, recurring times of the year.
-
D.
hasFloodProtectionInfrastructure
Indicates that there exists built or implemented infrastructure designed to protect against or mitigate flooding for the referenced entity.
-
E.
frequentNaturalHazard
Indicates that a location or area regularly experiences natural hazards such as floods, earthquakes, storms, or similar events with notable frequency.
- 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_69a8861acab88190bb43cde203429399 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69ab5c553e508190b0f511b05e07fa20 |
completed | March 6, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69aa61c25a648190892de94c997fb983 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:30 p.m.