Triple
T25142602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hoya Station |
E629842
|
entity |
| Predicate | connectsSuburbsTo |
P120418
|
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: [Hoya Station, connectsSuburbsTo, central Tokyo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsSuburbsTo Context triple: [Hoya Station, connectsSuburbsTo, central Tokyo]
-
A.
connectsSuburbWith
chosen
Indicates a relationship where something (such as a route, service, or infrastructure) links or provides direct access between a suburb and another place or area.
-
B.
connectsToSuburb
Indicates that one entity has a direct connection or link to a suburban area, such as via transport, infrastructure, or adjacency.
-
C.
connectsCityTo
Indicates a relationship in which a route, infrastructure, or link joins one city to another, enabling connection or interaction between them.
-
D.
hasSuburbAlong
Indicates that a larger area or route is associated with, or passes by, one or more suburbs located along its extent.
-
E.
servesSuburbsOf
Indicates that a service, route, or facility provides coverage or support to the suburban areas associated with a particular city or region.
- 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_69e2ff349e408190a6f4a5a66279f54d |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f65aa07c048190a5df30d53d8f0cf5 |
completed | May 2, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f659cc571c819097e51e531961d812 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 18, 2026, 6:29 a.m.