Triple
T18650947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christel Takigawa |
E455933
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object | 滝川クリステル |
—
|
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: 滝川クリステル | Statement: [Christel Takigawa, nativeName, 滝川クリステル]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 滝川クリステル Context triple: [Christel Takigawa, nativeName, 滝川クリステル]
-
A.
滝川クリステル
chosen
滝川クリステルは、日本のテレビ局アナウンサー出身でニュースキャスターや司会者として知られるフランス生まれのタレントです。
-
B.
Sara Takanashi
Sara Takanashi is a Japanese ski jumper and one of the most successful female athletes in the sport’s history, holding numerous World Cup victories and overall titles.
-
C.
Tanaka Rie
Tanaka Rie is a Japanese voice actress and singer known for her prominent roles in anime series such as "Love Hina," "Toradora!," and "Fate/stay night."
-
D.
Yumi Shirakawa
Yumi Shirakawa was a Japanese actress known for her prominent roles in 1950s and 1960s genre and drama films, including several classic Toho productions.
-
E.
Ayumi Nakamura
Ayumi Nakamura is a Japanese rock singer and songwriter known for her powerful vocals and energetic performances since the 1980s.
- 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_69d8d38ea1e88190997e9b231190ba6f |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e55010d27c8190aad8d3c9e8cd31b2 |
completed | April 19, 2026, 9:58 p.m. |
Created at: April 10, 2026, 11:47 a.m.