Triple
T30002063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saigoku Kannon Pilgrimage |
E762194
|
entity |
| Predicate | hasEndingPoint |
P390
|
FINISHED |
| Object | Kegon-ji |
—
|
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: Kegon-ji | Statement: [Saigoku Kannon Pilgrimage, hasEndingPoint, Kegon-ji]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEndingPoint Context triple: [Saigoku Kannon Pilgrimage, hasEndingPoint, Kegon-ji]
-
A.
hasEnding
Indicates that one entity concludes with, or terminates in, another entity (such as a specific substring, segment, or final component).
-
B.
canEndOn
Indicates that one entity is allowed or able to terminate, conclude, or finish with another specified entity or condition.
-
C.
hasLandmarkAtEnd
Indicates that a landmark is located at the terminal point or end of a specified path, route, or boundary.
-
D.
hasEnd
Indicates that one entity serves as the terminal point, boundary, or conclusion of another entity or process.
-
E.
endPoint
chosen
Indicates the terminal location, limit, or final state reached by an object, process, or path in a given relationship or action.
- 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_69f2246a47ac81909cf5213053687ffc |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f7805ce6208190ac6dbd9c97989978 |
completed | May 3, 2026, 5:05 p.m. |
| PD | Predicate disambiguation | batch_69f77956ec648190ba4fb7e9d83fd107 |
completed | May 3, 2026, 4:35 p.m. |
Created at: April 29, 2026, 6:41 p.m.