Triple
T3221012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Snowy Hydro Scheme |
E67510
|
entity |
| Predicate | numberOfAqueducts |
P46609
|
FINISHED |
| Object | 145 |
—
|
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: 145 | Statement: [Snowy Hydro Scheme, numberOfAqueducts, 145]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfAqueducts Context triple: [Snowy Hydro Scheme, numberOfAqueducts, 145]
-
A.
lengthOfMainAqueduct
Indicates the measured length of the primary aqueduct in a water conveyance system.
-
B.
hasMajorCanal
Indicates that one entity possesses or contains a primary canal or main waterway associated with it.
-
C.
numberOfFountains
Indicates the quantitative relationship specifying how many fountains are associated with a given entity.
-
D.
waterInfrastructure
Indicates the existence, development, or management of systems and facilities that supply, store, treat, or distribute water between entities.
-
E.
hasNumberOfBridges
Indicates the quantitative relationship specifying how many bridges are associated with a given 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_69ad858b8adc8190ad989712c87a476b |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adae16f20081909d7f3bac016f961d |
completed | March 8, 2026, 5:12 p.m. |
| PD | Predicate disambiguation | batch_69ad9e0bb6c48190a0659c67d40ee37c |
completed | March 8, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69ada148e9108190b363dd0f1a94ac8e |
completed | March 8, 2026, 4:18 p.m. |
Created at: March 8, 2026, 3:08 p.m.