Triple
T11749734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zeami Motokiyo |
E279373
|
entity |
| Predicate | wrote |
P2831
|
FINISHED |
| Object | Kadensho |
E944853
|
NE 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: Kadensho | Statement: [Zeami Motokiyo, wrote, Kadensho]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kadensho Context triple: [Zeami Motokiyo, wrote, Kadensho]
-
A.
Kadensho
chosen
Kadensho is a seminal treatise on Noh theatre aesthetics and performance theory traditionally attributed to the playwright and actor Zeami Motokiyo.
-
B.
Kutama
Kutama is a rural village in the Zvimba District of northern Zimbabwe, known primarily as the birthplace of former president Robert Mugabe.
-
C.
Kamenari
Kamenari is a small coastal village in Montenegro known for its ferry crossing and scenic location on the Bay of Kotor.
-
D.
Konedobu
Konedobu is a suburb of Port Moresby in Papua New Guinea, known for housing many government offices and administrative facilities.
-
E.
Kaiten
Kaiten was a Japanese warship that took part in the late-19th-century Boshin War naval engagements, including the Battle of Hakodate.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6ab01038c819080714901502c84fc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a508b0c4819082fbcc27d559ea2f |
completed | April 10, 2026, 7:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f0902f8c448190a71512353788ef09 |
completed | April 28, 2026, 10:47 a.m. |
Created at: April 8, 2026, 9:41 p.m.