Triple
T17733425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kokkai-gijidō-mae Station |
E442644
|
entity |
| Predicate | hasThroughPassengersWith |
P128797
|
FINISHED |
| Object | Nagatachō Station |
—
|
NE NERFINISHED |
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: Nagatachō Station | Statement: [Kokkai-gijidō-mae Station, hasThroughPassengersWith, Nagatachō Station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasThroughPassengersWith Context triple: [Kokkai-gijidō-mae Station, hasThroughPassengersWith, Nagatachō Station]
-
A.
hasPassengerRole
Indicates that an entity participates in a context or event specifically in the capacity or role of a passenger.
-
B.
passengers
Indicates that one entity is traveling in or being transported by another entity, typically as a non-operating occupant.
-
C.
hasPassengerUsageCategory
Indicates the classification of how a passenger-related resource or service is used (e.g., its usage type or category for passengers).
-
D.
hasPassengerOperator
Indicates that an entity (such as a vehicle or service) is operated by an organization or person responsible for carrying passengers.
-
E.
hasPassengerTrafficFrom
Indicates that an entity receives or handles passenger traffic originating from another entity.
- 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e478e86f188190a5dd7fb32fd04c7b |
completed | April 19, 2026, 6:40 a.m. |
| PD | Predicate disambiguation | batch_69e3cde815e08190881972e2d80d151e |
completed | April 18, 2026, 6:31 p.m. |
| PDg | Predicate description generation | batch_69e3d37ab6988190bd326ea6f8dd4aaa |
completed | April 18, 2026, 6:54 p.m. |
Created at: April 10, 2026, 10:08 a.m.