Triple
T22420515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Randenigala Dam |
E554231
|
entity |
| Predicate | connectedTo |
P37
|
FINISHED |
| Object | Rantembe Dam |
—
|
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: Rantembe Dam | Statement: [Randenigala Dam, connectedTo, Rantembe Dam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rantembe Dam Context triple: [Randenigala Dam, connectedTo, Rantembe Dam]
-
A.
Rantembe Dam
chosen
Rantembe Dam is a hydroelectric and irrigation dam in Sri Lanka that forms part of the Mahaweli River development scheme.
-
B.
Binga Dam
Binga Dam is a major hydroelectric dam in the Philippines that harnesses the flow of the Agno River for power generation and water management.
-
C.
Bariri Dam
Bariri Dam is a hydroelectric and river regulation structure located on Brazil’s Tietê River, contributing to regional power generation and water management.
-
D.
Wyangala Dam
Wyangala Dam is a major water storage and flood mitigation reservoir in New South Wales, Australia, serving irrigation, water supply, and recreational purposes.
-
E.
Masinga Dam
Masinga Dam is a major hydroelectric and water storage reservoir in Kenya that forms part of the Tana River hydropower cascade.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e4f2d0c819091aa3558ea2ee630 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1594a58508190b41fd16c8de5f8b4 |
completed | April 29, 2026, 1:05 a.m. |
Created at: April 16, 2026, 8:46 p.m.