Triple
T25518321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yoyogi Station |
E639571
|
entity |
| Predicate | adjacentStationOnChuoSobuLine |
P22113
|
FINISHED |
| Object | Shinjuku 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: Shinjuku Station | Statement: [Yoyogi Station, adjacentStationOnChuoSobuLine, Shinjuku Station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjacentStationOnChuoSobuLine Context triple: [Yoyogi Station, adjacentStationOnChuoSobuLine, Shinjuku Station]
-
A.
adjacentStationOnChuoLine
chosen
Indicates that two stations are directly next to each other as consecutive stops on the Chuo railway line.
-
B.
adjacentStationOnSaikyoLine
Indicates that one station is directly next to another station along the Saikyo railway line, with no other stations in between.
-
C.
adjacentStationOnSennichimaeLine
Indicates that one station is directly next to another station along the Sennichimae railway line.
-
D.
adjacentStationOnJRTōzaiLine
Indicates that one station is directly next to another station along the JR Tōzai Line, with no other stations in between.
-
E.
adjacentStationOnTokyuToyokoLine
Indicates that one station is directly next to another station along the Tokyu Toyoko railway line.
- 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_69e75dbe32e48190a62d749a0ff2a96a |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f661b58ac48190907b6c6e9ccc2c59 |
completed | May 2, 2026, 8:42 p.m. |
| PD | Predicate disambiguation | batch_69f660eea4648190b0d5e24293607813 |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 21, 2026, 2:58 p.m.