Triple
T4159962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canadair CL-215 |
E91506
|
entity |
| Predicate | waterCapacity |
P13057
|
FINISHED |
| Object | 5435 litres |
—
|
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: 5435 litres | Statement: [Canadair CL-215, waterCapacity, 5435 litres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterCapacity Context triple: [Canadair CL-215, waterCapacity, 5435 litres]
-
A.
waterVolume
chosen
Indicates the amount of water present in or associated with an entity, typically measured as a volume.
-
B.
reservoirTotalCapacity
Indicates the maximum volume of water that a reservoir is designed to hold when full.
-
C.
waterStorageOrgan
Indicates that one entity functions as an organ specialized for storing water for another entity.
-
D.
reservoirLiveStorageCapacity_m3
Indicates the volume of water that a reservoir can actively store and use, measured in cubic meters.
-
E.
reservoirGrossStorageCapacity_m3
Indicates the total volume of water a reservoir can hold when filled to its maximum designed storage level, measured in cubic meters.
- 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_69aed9626ebc8190a39de631788bea3e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0321eee88190871c1d4bf44a5007 |
completed | March 9, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69af018dc90c8190a754b1bfbc802e80 |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:44 p.m.