Triple
T27376782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kannai Station |
E691095
|
entity |
| Predicate | adjacentStationOnNegishiLine |
P172112
|
FINISHED |
| Object | Sakuragichō 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: Sakuragichō Station | Statement: [Kannai Station, adjacentStationOnNegishiLine, Sakuragichō Station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjacentStationOnNegishiLine Context triple: [Kannai Station, adjacentStationOnNegishiLine, Sakuragichō Station]
-
A.
adjacentStationOnSennichimaeLine
Indicates that one station is directly next to another station along the Sennichimae railway line.
-
B.
adjacentStationOnHibiyaLine
Indicates that one station is directly next to another station along the Hibiya Line, with no other stations in between.
-
C.
adjacentStationOnSaikyoLine
Indicates that one station is directly next to another station along the Saikyo railway line, with no other stations in between.
-
D.
adjacentStationOnTanimachiLine
Indicates that one station is directly next to another station along the Tanimachi subway line.
-
E.
adjacentStationOnGinzaLine
Indicates that one station is directly next to another station along the Ginza subway line, with no other stations in between.
- 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_69ef52022538819081f873d0c84a6dd6 |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f6a9603b208190b3533ea2b441514c |
completed | May 3, 2026, 1:48 a.m. |
| PD | Predicate disambiguation | batch_69f6a751d5e48190a77dcecbe7ef9f0b |
completed | May 3, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f6a8de0b948190ae333e9cd99cbf6c |
completed | May 3, 2026, 1:46 a.m. |
Created at: April 27, 2026, 12:21 p.m.