Triple
T17670993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mula Dam |
E440519
|
entity |
| Predicate | catchmentArea_km2 |
P15963
|
FINISHED |
| Object | 2224 |
—
|
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: 2224 | Statement: [Mula Dam, catchmentArea_km2, 2224]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: catchmentArea_km2 Context triple: [Mula Dam, catchmentArea_km2, 2224]
-
A.
catchmentArea
chosen
Indicates the geographic area from which something (such as a facility, service, or natural feature) draws or collects people, resources, or water.
-
B.
drainageAreaApprox
Indicates that one entity has an approximate drainage area measured or characterized by the other entity.
-
C.
hasCatchmentAreaSize
Indicates the size or extent of the geographic area from which something (e.g., a facility or service) draws its users, resources, or influence.
-
D.
meanSurfaceArea_km2
Indicates the average surface area of an entity measured in square kilometers.
-
E.
areaApproxKm2
Indicates that one entity has an approximate area, measured in square kilometers, given by the other entity.
- 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_69d8b9e87e18819087104a44dc4dc5b1 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46f68a038819084828ff73bcf1fcc |
completed | April 19, 2026, 6 a.m. |
| PD | Predicate disambiguation | batch_69e3cde007d8819090dd92eea9f022cc |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 9:59 a.m.