Triple
T7325136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katsuya Nomura |
E168851
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Katsuya |
E217933
|
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: Katsuya | Statement: [Katsuya Nomura, givenName, Katsuya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Katsuya Context triple: [Katsuya Nomura, givenName, Katsuya]
-
A.
Katsuya
chosen
Katsuya is a Japanese given name commonly used for males.
-
B.
Takeharu
Takeharu is a Japanese given name commonly used for males.
-
C.
Takahito
Takahito, better known by his title Prince Mikasa, was a member of the Japanese imperial family and the youngest son of Emperor Taishō.
-
D.
Kentarō
Kentarō is a Japanese given name commonly used for males, often associated with traditional or strong-sounding name combinations.
-
E.
Shintaro
Shintaro is a Japanese given name commonly used for males and borne by various notable figures in sports, entertainment, and politics.
- 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_69c68a54cacc81908e3b773441f19566 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f04993408190b73fb46d83a632d5 |
completed | March 27, 2026, 9:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c856a22b208190821bcbf21a074bb8 |
completed | March 28, 2026, 10:30 p.m. |
Created at: March 27, 2026, 3:03 p.m.