Triple
T34459021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Irohazaka Winding Road |
E884581
|
entity |
| Predicate | curveCountRelation |
P51537
|
FINISHED |
| Object | number of curves corresponds to characters of the Iroha poem |
—
|
LITERAL FINISHED |
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: number of curves corresponds to characters of the Iroha poem | Statement: [Irohazaka Winding Road, curveCountRelation, number of curves corresponds to characters of the Iroha poem]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: curveCountRelation Context triple: [Irohazaka Winding Road, curveCountRelation, number of curves corresponds to characters of the Iroha poem]
-
A.
relatedCurve
Indicates that one curve is associated with or derived from another curve in a defined relational way.
-
B.
numberOfCurves
chosen
Indicates the relationship that specifies how many distinct curves are associated with or contained in a given entity.
-
C.
degreeOfCurvesMentioned
Indicates that the specific degrees (or sharpness) of curves are explicitly referenced or discussed.
-
D.
curveOrder
Indicates the specific sequence or ranking assigned to curves within a set or system.
-
E.
curveName
Indicates that a specific curve is identified or labeled by a given name.
- 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_69f349c73a94819094dfcf50d00620b8 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7197a35d48190a108b2e55c32dff1 |
completed | May 3, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69f71824431081908d9685d2462ea242 |
completed | May 3, 2026, 9:40 a.m. |
Created at: May 1, 2026, 2 a.m.