Triple
T17706440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ichirō Matsui |
E441443
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Matsui |
—
|
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: Matsui | Statement: [Ichirō Matsui, familyName, Matsui]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matsui Context triple: [Ichirō Matsui, familyName, Matsui]
-
A.
Matsui
chosen
Matsui is a Japanese surname borne by various notable figures in fields such as politics, sports, and the military.
-
B.
Yūki Matsui
Yūki Matsui is a Japanese professional baseball pitcher known for his success as a closer in Nippon Professional Baseball and his move to Major League Baseball.
-
C.
Hideki Matsui
Hideki Matsui is a former Japanese professional baseball slugger who became a star outfielder and designated hitter in Major League Baseball, most notably with the New York Yankees.
-
D.
Yasuo Matsui
Yasuo Matsui was a Japanese-American architect active in early 20th-century New York City, known for his work on prominent skyscrapers.
-
E.
Mio Tanaka
Mio Tanaka is a Japanese actress known for her role in the kaiju film "Godzilla Minus One."
- 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_69d8b9ea20b48190ace88bb46b01e6a9 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e47297f7188190ba859d71e394bd4b |
completed | April 19, 2026, 6:13 a.m. |
Created at: April 10, 2026, 10:05 a.m.