Triple
T36064326
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lac de Vouglans |
E1043176
|
entity |
| Predicate | fillingOfReservoir |
P184535
|
FINISHED |
| Object | late 1960s |
—
|
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: late 1960s | Statement: [Lac de Vouglans, fillingOfReservoir, late 1960s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fillingOfReservoir Context triple: [Lac de Vouglans, fillingOfReservoir, late 1960s]
-
A.
reservoirLiveStorageCapacity_m3
Indicates the volume of water that a reservoir can actively store and use, measured in cubic meters.
-
B.
reservoir
Indicates that one entity serves as a storage or containment source (often for a resource) that can supply or affect another entity.
-
C.
reservoirTotalCapacity
Indicates the maximum volume of water that a reservoir is designed to hold when full.
-
D.
reservoirGrossStorageCapacity_m3
Indicates the total volume of water a reservoir can hold when filled to its maximum designed storage level, measured in cubic meters.
-
E.
reservoirType
Indicates the specific kind or classification of a reservoir associated with an entity.
- 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_69f76e2f09448190b0486d5ecad5e243 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7b35e32d481909ef0220e6f6ff4a8 |
completed | May 3, 2026, 8:43 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bad2e88190963ab4ee5d4f2038 |
completed | May 3, 2026, 8:36 p.m. |
| PDg | Predicate description generation | batch_69f7b2c66054819083897e25edb65ba7 |
completed | May 3, 2026, 8:40 p.m. |
Created at: May 3, 2026, 4:08 p.m.