Triple
T30640015
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 加藤 |
E779947
|
entity |
| Predicate | rankAmongJapaneseSurnames |
P86407
|
FINISHED |
| Object | high |
—
|
LITERAL 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: high | Statement: [加藤, rankAmongJapaneseSurnames, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankAmongJapaneseSurnames Context triple: [加藤, rankAmongJapaneseSurnames, high]
-
A.
hasJapaneseSurname
Indicates that the person or entity possesses a surname that is of Japanese origin or is commonly used in Japanese naming conventions.
-
B.
rankByCommonnessInJapan
chosen
Indicates how items are ordered based on how commonly they occur or are found in Japan.
-
C.
rankWithinJapan
Indicates the relative position or standing of something when compared only among counterparts within Japan.
-
D.
nameInJapaneseKana
Indicates that an entity’s name is written or represented using Japanese kana characters.
-
E.
JapaneseNameOrigin
Indicates that one entity’s name originates from or is derived from the Japanese language or naming tradition in relation to another entity.
- F. None of above.
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_69f224a50ebc81909b961a94c7f66b12 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68a5475f48190b0fcb96b90e470f2 |
completed | May 2, 2026, 11:35 p.m. |
| PD | Predicate disambiguation | batch_69f67e448a9c8190b591374d98799fe3 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 29, 2026, 8:29 p.m.