Triple
T11676311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keikyu Corporation |
E277499
|
entity |
| Predicate | parentTransportCategory |
P70905
|
FINISHED |
| Object | private railway (Japan) |
—
|
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: private railway (Japan) | Statement: [Keikyu Corporation, parentTransportCategory, private railway (Japan)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: parentTransportCategory Context triple: [Keikyu Corporation, parentTransportCategory, private railway (Japan)]
-
A.
busCategory
Indicates the classification or type of a bus within a defined categorization system.
-
B.
hasTransportCategory
chosen
Indicates that one entity is classified under a particular category or type of transport associated with another entity.
-
C.
primaryTransportModel
Indicates that one transport model is designated as the main or default model used for a given context or entity.
-
D.
transportType
Indicates the mode or means of transportation used in carrying something or someone from one place to another.
-
E.
transportRole
Indicates that an entity participates in a transportation process with a specific functional role (e.g., carrier, passenger, cargo, or operator).
- 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_69d6aafd0a448190b44da30af8c6c519 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a44504c48190b519765a83ff9c5e |
completed | April 10, 2026, 7:18 a.m. |
| PD | Predicate disambiguation | batch_69d88a77e6e88190b7519100bde76575 |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:40 p.m.