Triple
T9978598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kamyshin Reservoir |
E196392
|
entity |
| Predicate | hasVolumeUnit |
P12631
|
FINISHED |
| Object | cubic metre |
—
|
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: cubic metre | Statement: [Kamyshin Reservoir, hasVolumeUnit, cubic metre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVolumeUnit Context triple: [Kamyshin Reservoir, hasVolumeUnit, cubic metre]
-
A.
hasUnitOf
Indicates that a quantity, measurement, or value is expressed in terms of a specific unit.
-
B.
approximateVolumeInCubicCentimetres
Indicates that one entity has an estimated or roughly calculated volume measured in cubic centimetres.
-
C.
unitOfMeasure
chosen
Indicates that one entity specifies the standard unit in which the quantity or value of another entity is measured.
-
D.
hasLargeVolume
Indicates that an entity possesses or is characterized by a comparatively large physical or quantitative volume.
-
E.
typeOfUnit
Indicates that one entity specifies the kind or category of measurement unit that the other entity belongs to.
- 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_69ca82efbce081908179b4b9c65096eb |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb850bde48190a06b77757f8c081b |
completed | April 2, 2026, 12:29 a.m. |
| PD | Predicate disambiguation | batch_69cd1d9daa808190b413a1b9a1e929e2 |
completed | April 1, 2026, 1:29 p.m. |
Created at: March 30, 2026, 8:49 p.m.