Triple
T28813527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 濃尾平野 |
E727577
|
entity |
| Predicate | 交通の特徴 |
P55411
|
FINISHED |
| Object | 東海道新幹線沿線地域を含む |
—
|
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: 東海道新幹線沿線地域を含む | Statement: [濃尾平野, 交通の特徴, 東海道新幹線沿線地域を含む]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 交通の特徴 Context triple: [濃尾平野, 交通の特徴, 東海道新幹線沿線地域を含む]
-
A.
transportationCharacteristic
chosen
Indicates a specific property, feature, or quality that characterizes a mode, means, or instance of transportation.
-
B.
transportCharacteristic
Indicates a relationship where a specific characteristic, property, or feature is attributed to a mode or instance of transport.
-
C.
mobilityCharacteristic
Indicates a relationship where an entity is described or classified in terms of its movement or transportation-related properties, such as how, how well, or under what conditions it can move or be moved.
-
D.
transportInfrastructureFeature
Indicates a relationship where an entity is a specific element or component of transport infrastructure, such as roads, railways, or related facilities.
-
E.
hasRoadCharacteristics
Indicates that one entity possesses specific road-related features or attributes, such as type, condition, or structural properties.
- 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_69f0319c38948190bca746ad60fd25ba |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f658f163a88190b1dd222eaa0f93ea |
completed | May 2, 2026, 8:05 p.m. |
| PD | Predicate disambiguation | batch_69f65762b5e481908a30ca963dcba4be |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 28, 2026, 6:32 a.m.