Triple
T35319246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karasuma-dori |
E1019990
|
entity |
| Predicate | hasStationAlong |
P201282
|
FINISHED |
| Object | Shijo 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: Shijo Station | Statement: [Karasuma-dori, hasStationAlong, Shijo Station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStationAlong Context triple: [Karasuma-dori, hasStationAlong, Shijo Station]
-
A.
hasStationAt
Indicates that an entity maintains or operates a station located at a specified place.
-
B.
hasStationNear
Indicates that one entity has a station located in close proximity to another entity.
-
C.
isStationOf
Indicates that a given location functions as a station (e.g., transport or service hub) associated with or serving a particular system, line, route, or organization.
-
D.
hasStationInCity
Indicates that a station or facility is located within a particular city.
-
E.
hasInterchangeStationWith
Indicates that two transportation lines, routes, or systems share a station where passengers can transfer between them.
- 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_69f76de9d45c81908a2ed0956b448b65 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ffe613c03481909f3043ec8bf0bed9 |
completed | May 10, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_69ffe4a73fb4819091600725a443981a |
completed | May 10, 2026, 1:51 a.m. |
| PDg | Predicate description generation | batch_69ffe6130698819099328fce92bb2784 |
completed | May 10, 2026, 1:57 a.m. |
Created at: May 3, 2026, 4:03 p.m.