Triple
T11749705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zeami Motokiyo |
E279373
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Motokiyo
Motokiyo is the given name of Zeami Motokiyo, the seminal Japanese playwright, actor, and theorist who shaped the classical Noh theatre tradition.
|
E949564
|
NE FINISHED |
How this triple was built (4 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: Motokiyo | Statement: [Zeami Motokiyo, givenName, Motokiyo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Motokiyo Context triple: [Zeami Motokiyo, givenName, Motokiyo]
-
A.
Nagako
Nagako, better known as Empress Kōjun, was the long-serving consort of Emperor Shōwa (Hirohito) and the mother of Emperor Emeritus Akihito of Japan.
-
B.
Nijō Motoko
Nijō Motoko was a Japanese noblewoman of the Nijō family and the mother of Empress Teimei, consort of Emperor Taishō.
-
C.
Nijō Tsuruko
Nijō Tsuruko was a Japanese noblewoman of the Nijō family and the mother of Empress Shōken, consort of Emperor Meiji.
-
D.
Yuriko
Yuriko is the given name of Japanese actress Rinko Kikuchi, known for her roles in films such as "Babel" and "Pacific Rim."
-
E.
Kunitachi
Kunitachi is a suburban city in western Tokyo, Japan, known for its universities, tree-lined avenues, and residential character.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Motokiyo Triple: [Zeami Motokiyo, givenName, Motokiyo]
Generated description
Motokiyo is the given name of Zeami Motokiyo, the seminal Japanese playwright, actor, and theorist who shaped the classical Noh theatre tradition.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Motokiyo Target entity description: Motokiyo is the given name of Zeami Motokiyo, the seminal Japanese playwright, actor, and theorist who shaped the classical Noh theatre tradition.
-
A.
Nagako
Nagako, better known as Empress Kōjun, was the long-serving consort of Emperor Shōwa (Hirohito) and the mother of Emperor Emeritus Akihito of Japan.
-
B.
Nijō Motoko
Nijō Motoko was a Japanese noblewoman of the Nijō family and the mother of Empress Teimei, consort of Emperor Taishō.
-
C.
Nijō Tsuruko
Nijō Tsuruko was a Japanese noblewoman of the Nijō family and the mother of Empress Shōken, consort of Emperor Meiji.
-
D.
Yuriko
Yuriko is the given name of Japanese actress Rinko Kikuchi, known for her roles in films such as "Babel" and "Pacific Rim."
-
E.
Kunitachi
Kunitachi is a suburban city in western Tokyo, Japan, known for its universities, tree-lined avenues, and residential character.
- F. None of above. chosen
Provenance (5 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_69f16695479c819082c6ab12657a2d5f |
completed | April 29, 2026, 2:01 a.m. |
| NEDg | Description generation | batch_69f16e31ebfc81908255e24b96bf9a99 |
completed | April 29, 2026, 2:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f1a09eae7481908200709ae9721d53 |
completed | April 29, 2026, 6:09 a.m. |
Created at: April 8, 2026, 9:41 p.m.