Triple
T13455765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kō Shibasaki |
E311227
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Yukie |
E575154
|
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: Yukie | Statement: [Kō Shibasaki, givenName, Yukie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yukie Context triple: [Kō Shibasaki, givenName, Yukie]
-
A.
Yukie
chosen
Yukie is a Japanese film featuring Ken Watanabe in a prominent role.
-
B.
Yuko
Yuko is an alternate name for the Yukpa language, an indigenous language spoken by the Yukpa people of Colombia and Venezuela.
-
C.
Yuko
Yuko is a common Japanese feminine given name borne by numerous notable figures in fields such as entertainment, sports, and the arts.
-
D.
Yukari Sugi
Yukari Sugi is a Japanese actress and the former wife of acclaimed actor Ken Watanabe.
-
E.
Takako
Takako is a Japanese feminine given name borne by various notable figures in politics, arts, and entertainment.
- 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_69d806a938b8819097ec43a2229fc7f9 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaefc52448190b30d7999f44a9765 |
completed | April 12, 2026, 2:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f76ba344e0819098da09416a913851 |
completed | May 3, 2026, 3:37 p.m. |
Created at: April 9, 2026, 9:41 p.m.