Triple
T18584294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tengen Toppa Gurren Lagann |
E454197
|
entity |
| Predicate | hasMainCharacter |
P1183
|
FINISHED |
| Object | Yoko Littner |
—
|
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: Yoko Littner | Statement: [Tengen Toppa Gurren Lagann, hasMainCharacter, Yoko Littner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yoko Littner Context triple: [Tengen Toppa Gurren Lagann, hasMainCharacter, Yoko Littner]
-
A.
Yoko Littner
chosen
Yoko Littner is a prominent, sharp-shooting heroine from the anime series "Tengen Toppa Gurren Lagann," known for her combat skills, distinctive appearance, and strong-willed personality.
-
B.
Yoko
Yoko is a Japanese given name commonly used for women and borne by various notable figures in arts, literature, and entertainment.
-
C.
Yoko Tsukasa
Yoko Tsukasa is a Japanese actress best known internationally for her role in Akira Kurosawa’s samurai film "Yojimbo."
-
D.
Yoko Sugiyama
Yoko Sugiyama was the wife of renowned Japanese author and playwright Yukio Mishima.
-
E.
Yoko Satō
Yoko Satō is a Japanese individual known for bearing the surname Satō, which is one of the most common family names in Japan.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d8d38ae7e081908a98df1251842402 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e543d200dc8190b8797d731f4e4865 |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 11:44 a.m.