Triple
T34443349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 柳宗悦 |
E884153
|
entity |
| Predicate | knownFor |
P22
|
FINISHED |
| Object | 無名の職人による日常の工芸品の美の発見 |
—
|
LITERAL FINISHED |
How this triple was built (1 step)
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: 無名の職人による日常の工芸品の美の発見 | Statement: [柳宗悦, knownFor, 無名の職人による日常の工芸品の美の発見]
Provenance (2 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_69f7194bcec88190a0f36937b0eff669 |
completed | May 3, 2026, 9:45 a.m. |
Created at: May 1, 2026, 2 a.m.