Triple
T34443340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 柳宗悦 |
E884153
|
entity |
| Predicate | alternativeReading |
P181379
|
FINISHED |
| Object | やなぎ むねよし |
—
|
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: やなぎ むねよし | Statement: [柳宗悦, alternativeReading, やなぎ むねよし]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alternativeReading Context triple: [柳宗悦, alternativeReading, やなぎ むねよし]
-
A.
alternativeReader
Indicates that one entity serves as an alternative or substitute reader for another entity or resource.
-
B.
readingAid
Indicates that one entity assists or facilitates another entity’s ability to read or engage in reading activities.
-
C.
reading
Indicates that an entity is engaged in the activity of interpreting and understanding written or printed material from another entity or source.
-
D.
readingFeature
Indicates that an entity possesses a characteristic, capability, or attribute specifically related to reading.
-
E.
readingOf
Indicates that one entity is an interpretation, measurement, or recorded value derived from another entity.
- 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_69f349c548d88190978e2a82502c03d0 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7688dd3d08190ad13d0e780570a1c |
completed | May 3, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69f767fcf2f881908bacc7bfc38e68a5 |
completed | May 3, 2026, 3:21 p.m. |
| PDg | Predicate description generation | batch_69f7688cea58819098bdfd7c80df7634 |
completed | May 3, 2026, 3:23 p.m. |
Created at: May 1, 2026, 2 a.m.