Triple
T29294251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yoko Sugiyama |
E742776
|
entity |
| Predicate | marriedToRenownedAuthor |
P29616
|
FINISHED |
| Object | Yukio Mishima |
—
|
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: Yukio Mishima | Statement: [Yoko Sugiyama, marriedToRenownedAuthor, Yukio Mishima]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriedToRenownedAuthor Context triple: [Yoko Sugiyama, marriedToRenownedAuthor, Yukio Mishima]
-
A.
hasAuthorMarriedName
Indicates that an author’s married surname or full married name is associated with them, typically differing from their birth or maiden name.
-
B.
hasAuthorSpouse
Indicates that the spouse of the subject entity is the author of the related work or entity.
-
C.
marriedToBeforeFameOf
Indicates that one person was married to another person before the latter became famous.
-
D.
marriedToPoet
Indicates that one person is married to another person who is a poet.
-
E.
marriedToNotablePerson
chosen
Indicates that a person is legally married to another individual who is widely recognized or notable.
- 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_69f0912323c48190b9a24ef8cf359225 |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f73223675481908c1bc3208c0f5284 |
completed | May 3, 2026, 11:31 a.m. |
| PD | Predicate disambiguation | batch_69f7317690108190b3aae2cd2e1d069e |
completed | May 3, 2026, 11:28 a.m. |
Created at: April 28, 2026, 1:04 p.m.