Triple
T24760342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kawanishi-Ikeda Station |
E619417
|
entity |
| Predicate | isImportantStopOn |
P29762
|
FINISHED |
| Object | JR Takarazuka Line |
—
|
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: JR Takarazuka Line | Statement: [Kawanishi-Ikeda Station, isImportantStopOn, JR Takarazuka Line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isImportantStopOn Context triple: [Kawanishi-Ikeda Station, isImportantStopOn, JR Takarazuka Line]
-
A.
isImportantFor
Indicates that something holds significant value, relevance, or necessity in relation to something else.
-
B.
majorStop
chosen
Indicates that a location functions as a primary or significant stop along a route or service path, typically where vehicles regularly halt for boarding, alighting, or key operations.
-
C.
isSmallStop
Indicates that something functions as a minor or less significant stop within a route, sequence, or process.
-
D.
isSacredStopOn
Indicates that a particular location or stop is regarded as sacred or holy within the context of a route, journey, or path.
-
E.
isNonStop
Indicates that a service, trip, or process occurs from start to finish without any intermediate stops or interruptions.
- 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_69e2fabbea94819092ed41348909622f |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f42d9000b8819081ea2605f3c193d6 |
completed | May 1, 2026, 4:35 a.m. |
| PD | Predicate disambiguation | batch_69f420f471a0819095a6cd24ed8f7476 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 4:27 a.m.