Triple
T14237665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hokkaido Shinkansen |
E352926
|
entity |
| Predicate | bridgeBetweenRegions |
P24718
|
FINISHED |
| Object | Tohoku region and Hokkaido |
—
|
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: Tohoku region and Hokkaido | Statement: [Hokkaido Shinkansen, bridgeBetweenRegions, Tohoku region and Hokkaido]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bridgeBetweenRegions Context triple: [Hokkaido Shinkansen, bridgeBetweenRegions, Tohoku region and Hokkaido]
-
A.
bridgeLocation
Indicates the specific place or area where a bridge is situated or spans.
-
B.
connectsRegions
chosen
Indicates a relationship where one entity links or joins two or more distinct regions, enabling passage, interaction, or continuity between them.
-
C.
bridgesBetween
Indicates a relationship where something connects or links two otherwise separate entities, contexts, or states, enabling interaction or transition between them.
-
D.
bridgeName
Indicates the designated name assigned to a specific bridge.
-
E.
crossBorderRegion
Indicates a region that spans or intersects the boundary between two or more distinct territorial or jurisdictional areas.
- 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_69d8278adc7c8190a9218d69bce3c4e6 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de62422e28819089e7115052a28c96 |
completed | April 14, 2026, 3:50 p.m. |
| PD | Predicate disambiguation | batch_69de05bf069c8190b69f00f00f5eb126 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:08 a.m.