Triple
T38567801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenji Matsui |
E928274
|
entity |
| Predicate | nameInJapaneseRomanization |
P164578
|
FINISHED |
| Object | Kenji 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: Kenji Matsui | Statement: [Kenji Matsui, nameInJapaneseRomanization, Kenji Matsui]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameInJapaneseRomanization Context triple: [Kenji Matsui, nameInJapaneseRomanization, Kenji Matsui]
-
A.
nameInJapaneseKana
Indicates that an entity’s name is written or represented using Japanese kana characters.
-
B.
nameInLanguageRomanization
chosen
Indicates that an entity’s name is represented in the romanized (Latin-script) form of a particular language.
-
C.
hasNameInJapanese
Indicates that an entity is associated with a specific name expressed in the Japanese language.
-
D.
officialNameInRomaji
Indicates that an entity’s official name is written using the Roman alphabet (romaji) representation.
-
E.
nameInMcCuneReischauer
Indicates that an entity’s name is represented using the McCune–Reischauer romanization system.
- 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_69f76eb8d1808190a588af29d8b266d6 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdaa36f90819093f8661969990c7d |
completed | May 7, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69fcd8fefc588190b063d7ea1ec87b07 |
completed | May 7, 2026, 6:25 p.m. |
Created at: May 3, 2026, 4:32 p.m.