Triple
T16068739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hakata–Shin-Yatsushiro |
E389803
|
entity |
| Predicate | railwayCategory |
P98797
|
FINISHED |
| Object | Shinkansen line section |
—
|
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: Shinkansen line section | Statement: [Hakata–Shin-Yatsushiro, railwayCategory, Shinkansen line section]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railwayCategory Context triple: [Hakata–Shin-Yatsushiro, railwayCategory, Shinkansen line section]
-
A.
trainsCategory
Indicates that one entity is a category or type under which the other entity is trained or classified.
-
B.
railwayClass
chosen
Indicates the specific classification or category assigned to a railway or railway service within a defined system.
-
C.
railwayStationCategory
Indicates the classification or type category assigned to a railway station within a rail network or system.
-
D.
railroadClass
Indicates the classification or category of a railroad according to an established system (e.g., by size, revenue, or regulatory status).
-
E.
railwayUse
Indicates that something is used as, or functions in the capacity of, a railway or rail-based transportation facility.
- 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_69d86daf32ec8190a8c0466c8f49c3c0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1858a00888190b8505071575dc56f |
completed | April 17, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e18272f2288190a17d45fb01cc2b07 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 4:57 a.m.