Triple
T12833269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sayano–Shushenskaya Dam |
E306839
|
entity |
| Predicate | averageAnnualGeneration |
P107138
|
FINISHED |
| Object | about 23.5 TWh |
—
|
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: about 23.5 TWh | Statement: [Sayano–Shushenskaya Dam, averageAnnualGeneration, about 23.5 TWh]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageAnnualGeneration Context triple: [Sayano–Shushenskaya Dam, averageAnnualGeneration, about 23.5 TWh]
-
A.
expectedAnnualGeneration
Indicates the amount of output (typically energy or production) that a system or asset is expected to generate over the course of a year.
-
B.
recordAnnualGenerationYear
Indicates the year in which an entity’s annual generation (e.g., production or output) is recorded.
-
C.
averageHouseholdsPoweredPerYear
Indicates the typical number of households that can be supplied with power over the course of one year.
-
D.
powerplantOutput
Indicates the amount of energy or power produced by a power plant over a given period or at a specific moment.
-
E.
grossElectricalCapacity_MWe
Indicates the total electrical power output capacity of a generating unit, measured in megawatts electric (MWe), before accounting for internal power consumption or losses.
- 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_69d7bdf52b94819096d6f0ba4ab50a98 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9714208f881908f7f8a921362909a |
completed | April 10, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69d96fa08cd481909a946046ba63809f |
completed | April 10, 2026, 9:46 p.m. |
| PDg | Predicate description generation | batch_69d9713e45a88190acd346f066093550 |
completed | April 10, 2026, 9:53 p.m. |
Created at: April 9, 2026, 5:34 p.m.