Triple
T25016285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keio Corporation Railway Division |
E626140
|
entity |
| Predicate | languageOfPassengerInformation |
P82602
|
FINISHED |
| Object | 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: Japanese | Statement: [Keio Corporation Railway Division, languageOfPassengerInformation, Japanese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfPassengerInformation Context triple: [Keio Corporation Railway Division, languageOfPassengerInformation, Japanese]
-
A.
languageOfSurroundingCountry
Indicates that a language is the primary or commonly used language in the country surrounding a given place or region.
-
B.
languageOfOnboardOperations
Indicates the language used to conduct or manage onboard operations.
-
C.
airlinePrimaryLanguage
Indicates the main language used by an airline for its official communication and operations.
-
D.
languageOfOfficialGuides
Indicates the language in which official guides or instructional materials are provided or published.
-
E.
navigationLanguage
chosen
Indicates the language used for navigation-related content, such as menus, directions, or interface controls.
- 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_69e2ff27755881908490178e83701160 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f66c5c13808190887180099745673b |
completed | May 2, 2026, 9:27 p.m. |
| PD | Predicate disambiguation | batch_69f66abddc448190a488852f8abdeb2c |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 18, 2026, 6:06 a.m.