Triple
T30364598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tachikawa, Tokyo |
E772381
|
entity |
| Predicate | monorailStation |
P169120
|
FINISHED |
| Object | Tachikawa-Kita 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: Tachikawa-Kita Station | Statement: [Tachikawa, Tokyo, monorailStation, Tachikawa-Kita Station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: monorailStation Context triple: [Tachikawa, Tokyo, monorailStation, Tachikawa-Kita Station]
-
A.
monorailLines
Indicates that there is a monorail transit line or system associated with, serving, or present in the referenced entity.
-
B.
monorailOpeningDate
Indicates the calendar date on which a monorail system or line was first opened for public operation.
-
C.
subwayStation
Indicates that one entity is a subway station associated with, located in, or serving the other entity.
-
D.
lightRailStation
Indicates that the subject is a light rail station or location designated for light rail transit services.
-
E.
lightRailStationName
Indicates that a light rail station has the specified name.
- 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_69f2248d71408190aec0d5c2001b1cff |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6827ecae8819092c15bbb1529dbad |
completed | May 2, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69f678d019fc8190913662cd2f87b857 |
completed | May 2, 2026, 10:21 p.m. |
| PDg | Predicate description generation | batch_69f679496c188190ba585792f987a1f4 |
completed | May 2, 2026, 10:23 p.m. |
Created at: April 29, 2026, 7:58 p.m.