Triple
T21376346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hankyu Imazu Line |
E527214
|
entity |
| Predicate | hasRouteInformation |
P144018
|
FINISHED |
| Object | available in Japanese |
—
|
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: available in Japanese | Statement: [Hankyu Imazu Line, hasRouteInformation, available in Japanese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRouteInformation Context triple: [Hankyu Imazu Line, hasRouteInformation, available in Japanese]
-
A.
hasRoute
Indicates that there exists a path or connection enabling travel or communication from one entity to another.
-
B.
hasRouteFeature
Indicates that a route possesses or is associated with a specific characteristic, attribute, or feature.
-
C.
hasRouteNetwork
Indicates that one entity possesses, is associated with, or is covered by a specific route network connecting multiple locations or paths.
-
D.
hasRouteMaps
Indicates that one entity possesses or provides route maps that describe paths, directions, or connections related to another entity.
-
E.
hasRouteDirection
Indicates that a specified route is associated with a particular travel direction (e.g., inbound, outbound, northbound).
- 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_69e0b51e80808190ba5cb05667af02a9 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69ee62c9494081909efa74e189454dc6 |
completed | April 26, 2026, 7:08 p.m. |
| PD | Predicate disambiguation | batch_69e6162bbfc88190a3e75859941b2638 |
completed | April 20, 2026, 12:03 p.m. |
| PDg | Predicate description generation | batch_69e61b3e47f881908fb2aac9bd2bfb58 |
completed | April 20, 2026, 12:25 p.m. |
Created at: April 16, 2026, 5:11 p.m.