Triple
T35206119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saga-Arashiyama Station |
E1016537
|
entity |
| Predicate | adjacentStationOnSaganoLine |
P191042
|
FINISHED |
| Object | Uzumasasa 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: Uzumasasa Station | Statement: [Saga-Arashiyama Station, adjacentStationOnSaganoLine, Uzumasasa Station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjacentStationOnSaganoLine Context triple: [Saga-Arashiyama Station, adjacentStationOnSaganoLine, Uzumasasa Station]
-
A.
adjacentStationOnSennichimaeLine
Indicates that one station is directly next to another station along the Sennichimae 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.
adjacentStationOnSakurajimaLine
Indicates that one station is directly next to another station along the Sakurajima railway line, with no other stations in between.
-
D.
adjacentStationOnKarasumaLine
Indicates that one station is directly next to another station along the Karasuma railway line.
-
E.
adjacentStationOnTsurumaiLine
Indicates that one station is directly next to another station along the Tsurumai 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_69f76ddf549c8190869d0af076fd2c28 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fcd867f36081908c88c55a6a1404c1 |
completed | May 7, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f47b188190b4cf4b4c748d9d03 |
completed | May 7, 2026, 5:55 p.m. |
| PDg | Predicate description generation | batch_69fcd866dd248190bff61c43bee93f54 |
completed | May 7, 2026, 6:22 p.m. |
Created at: May 3, 2026, 4:02 p.m.