Triple
T19806741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sasazuka Station |
E475831
|
entity |
| Predicate | adjacentStationOnKeioLine |
P137395
|
FINISHED |
| Object | Daitabashi 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: Daitabashi Station | Statement: [Sasazuka Station, adjacentStationOnKeioLine, Daitabashi Station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjacentStationOnKeioLine Context triple: [Sasazuka Station, adjacentStationOnKeioLine, Daitabashi Station]
-
A.
adjacentStationOnKeioInokashiraLine
Indicates that one station is directly next to another station along the Keio Inokashira railway line, with no other stations in between.
-
B.
adjacentStationOnKodomonokuniLine
Indicates that one station is directly next to another station along the Kodomonokuni railway line.
-
C.
adjacentStationOnTokyuToyokoLine
Indicates that one station is directly next to another station along the Tokyu Toyoko railway line.
-
D.
adjacentStationOnSaikyoLine
Indicates that one station is directly next to another station along the Saikyo railway line, with no other stations in between.
-
E.
adjacentStationOnJRKyotoLine
Indicates that one station is directly next to another station along the JR Kyoto railway 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65428f5c48190be6ae0d6a77675d2 |
completed | April 20, 2026, 4:28 p.m. |
| PD | Predicate disambiguation | batch_69e5305858108190bbbfdb9ba3ab9f80 |
completed | April 19, 2026, 7:43 p.m. |
| PDg | Predicate description generation | batch_69e532bcf41c8190b685b5adf46a60fc |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 1:49 p.m.