Triple
T30640043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 加藤 |
E779947
|
entity |
| Predicate | romanizedOrder |
P173422
|
FINISHED |
| Object | comes after given name in Western order |
—
|
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: comes after given name in Western order | Statement: [加藤, romanizedOrder, comes after given name in Western order]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: romanizedOrder Context triple: [加藤, romanizedOrder, comes after given name in Western order]
-
A.
romanizedUnder
Indicates that one written form is a romanized representation (using the Latin alphabet) of another form written in a different script.
-
B.
romanizedCenter
Indicates that one entity is the central or primary romanized (Latin-script) representation associated with another entity.
-
C.
romanizationType
Indicates the specific system or method used to convert text from one writing system into its Roman (Latin) alphabet representation.
-
D.
nameInLanguageRomanization
Indicates that an entity’s name is represented in the romanized (Latin-script) form of a particular language.
-
E.
nameOrderInJapan
Indicates that the person’s name is written or presented in the Japanese order, with the family name appearing before the given name.
- F. None of above. chosen
Provenance (4 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_69f6b56ed31481908c3e5d749e46bad9 |
completed | May 3, 2026, 2:39 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a7bdb481908d16a32f49e38c2c |
completed | May 3, 2026, 2:32 a.m. |
| PDg | Predicate description generation | batch_69f6b49339048190b617a6749f648825 |
completed | May 3, 2026, 2:36 a.m. |
Created at: April 29, 2026, 8:29 p.m.