Triple
T21525787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JS17 |
E531091
|
entity |
| Predicate | associatedStationNameRomaji |
P71490
|
FINISHED |
| Object | Ōsaki-eki |
—
|
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: Ōsaki-eki | Statement: [JS17, associatedStationNameRomaji, Ōsaki-eki]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedStationNameRomaji Context triple: [JS17, associatedStationNameRomaji, Ōsaki-eki]
-
A.
officialNameInRomaji
chosen
Indicates that an entity’s official name is written using the Roman alphabet (romaji) representation.
-
B.
nameInJapaneseKana
Indicates that an entity’s name is written or represented using Japanese kana characters.
-
C.
adjacentStationOnNambuLine
Indicates that one station is directly next to another station along the Nambu railway line, with no other stations in between.
-
D.
adjacentStationOnTokaidoShinkansen
Indicates that one station is directly next to another along the Tokaido Shinkansen line, with no other station in between.
-
E.
railwayStationAlsoKnownAs
Indicates that a railway station is referred to by an alternative name or alias.
- 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_69e0c45d95a081908e7962ad215da746 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee885073888190ae49f967f72acbf8 |
completed | April 26, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69e6320043bc81909417c41a718652ba |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:26 p.m.