Triple
T28130114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo University of the Arts |
E711041
|
entity |
| Predicate | nativeNameRomaji |
P164578
|
FINISHED |
| Object | Tōkyō Geijutsu Daigaku |
—
|
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: Tōkyō Geijutsu Daigaku | Statement: [Tokyo University of the Arts, nativeNameRomaji, Tōkyō Geijutsu Daigaku]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nativeNameRomaji Context triple: [Tokyo University of the Arts, nativeNameRomaji, Tōkyō Geijutsu Daigaku]
-
A.
officialNameInRomaji
Indicates that an entity’s official name is written using the Roman alphabet (romaji) representation.
-
B.
nameInLanguageRomanization
chosen
Indicates that an entity’s name is represented in the romanized (Latin-script) form of a particular language.
-
C.
nameInJapaneseKana
Indicates that an entity’s name is written or represented using Japanese kana characters.
-
D.
JapaneseNameReading
Indicates that one entity is the reading or pronunciation (e.g., in kana or romaji) of a Japanese name represented by the other entity.
-
E.
romanizationVariantOf
Indicates that one written form is a different romanized representation of the same underlying word or expression as another.
- 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_69ef9b73bd288190a21ae3d6aa14f386 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f6562fd3488190be1acd8c526a28d2 |
completed | May 2, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69f651a931748190a637e631a52bbfaa |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 27, 2026, 9:22 p.m.