Triple
T34545181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vidraru Dam |
E886904
|
entity |
| Predicate | maximumDepthOfReservoir |
P42760
|
FINISHED |
| Object | 155 metres |
—
|
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: 155 metres | Statement: [Vidraru Dam, maximumDepthOfReservoir, 155 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumDepthOfReservoir Context triple: [Vidraru Dam, maximumDepthOfReservoir, 155 metres]
-
A.
maximumWaterDepth
chosen
Indicates the greatest depth of water present or allowed in a given context, such as a location, container, or body of water.
-
B.
lakeMaximumDepth
Indicates the greatest recorded vertical distance from the lake’s surface to its deepest point.
-
C.
reservoirLength
Indicates the measured longitudinal extent of a reservoir from one end to the other.
-
D.
reservoirTotalCapacity
Indicates the maximum volume of water that a reservoir is designed to hold when full.
-
E.
fillingOfReservoir
Indicates that an action or process is filling a reservoir with a substance (typically a liquid such as water).
- 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_69f349ce5eb881909e431c670944aa68 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fd19f791f48190bbb6f6047f9ddc59 |
completed | May 7, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69fd0df365948190bc9bfc7ffd46acd8 |
completed | May 7, 2026, 10:10 p.m. |
Created at: May 1, 2026, 2:02 a.m.