Triple
T24989824
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | T-10 |
E625414
|
entity |
| Predicate | associatedStationJapaneseName |
P9882
|
FINISHED |
| Object | 日本橋駅 |
—
|
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: 日本橋駅 | Statement: [T-10, associatedStationJapaneseName, 日本橋駅]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedStationJapaneseName Context triple: [T-10, associatedStationJapaneseName, 日本橋駅]
-
A.
adjacentStationOnTokaidoShinkansen
Indicates that one station is directly next to another along the Tokaido Shinkansen line, with no other station in between.
-
B.
adjacentStationOnTokaidoMainLine
Indicates that one station is directly next to another station along the Tokaido Main Line, with no other stations in between.
-
C.
associatedStation
Indicates a relationship where one entity is linked or connected to a particular station as its relevant or related station.
-
D.
hasOfficialNameInJapanese
chosen
Indicates that an entity has an official, formally recognized name expressed in the Japanese language.
-
E.
adjacentStationOnNambuLine
Indicates that one station is directly next to another station along the Nambu railway line, with no other stations in between.
- 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_69e2ff2611c081908710457fbe6d376b |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f6db1f3ec48190a82e7d893d3c76ba |
completed | May 3, 2026, 5:20 a.m. |
| PD | Predicate disambiguation | batch_69f6d82adfa481908a5e196d2e18c73f |
completed | May 3, 2026, 5:07 a.m. |
Created at: April 18, 2026, 6:03 a.m.