Triple
T3221011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Snowy Hydro Scheme |
E67510
|
entity |
| Predicate | numberOfMajorTunnels |
P46608
|
FINISHED |
| Object | 7 |
—
|
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: 7 | Statement: [Snowy Hydro Scheme, numberOfMajorTunnels, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMajorTunnels Context triple: [Snowy Hydro Scheme, numberOfMajorTunnels, 7]
-
A.
hasMajorRailLinksTo
Indicates that there are significant railway connections or routes between two locations.
-
B.
SeikanTunnelConnects
Indicates that the Seikan Tunnel serves as a physical connection between two geographic locations or regions.
-
C.
bridgeAndTunnelRatio
Indicates the proportion between the number or extent of bridges and tunnels within a given system, network, or area.
-
D.
hasMilitaryTunnels
Indicates that one location possesses or contains underground tunnels used for military purposes in relation to another entity.
-
E.
SeikanTunnelType
Indicates that one entity is classified as a specific type or category of Seikan Tunnel.
- 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.