Triple
T12887330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nishi-Kawaguchi Station |
E308262
|
entity |
| Predicate | servedAsCommuterRouteTo |
P61070
|
FINISHED |
| Object | central Tokyo |
—
|
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: central Tokyo | Statement: [Nishi-Kawaguchi Station, servedAsCommuterRouteTo, central Tokyo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedAsCommuterRouteTo Context triple: [Nishi-Kawaguchi Station, servedAsCommuterRouteTo, central Tokyo]
-
A.
commuterServiceTo
Indicates a transportation service that regularly carries commuters to a specified destination.
-
B.
commuterDestination
chosen
Indicates that a location serves as the endpoint or target place to which a person regularly travels for commuting.
-
C.
commutesBetween
Indicates a regular pattern of travel back and forth between two locations, typically for work, study, or routine activities.
-
D.
operatesCommuterServiceBetween
Indicates that an entity runs a commuter transportation service connecting two specified locations.
-
E.
hasCommuterOrientation
Indicates that an entity is designed or intended primarily for use by commuters, emphasizing suitability for regular travel between home and work or study.
- 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_69d7bdf7c1f0819098102569a8d8cbf5 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97c7f91d08190aac2f6419d3ba992 |
completed | April 10, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69d96fa55b888190ab1612e93c41aec4 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:39 p.m.