Triple
T24593768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sakizaya people |
E608607
|
entity |
| Predicate | hasEthnonymInJapanese |
P28734
|
FINISHED |
| Object | サキザヤ族 |
—
|
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: サキザヤ族 | Statement: [Sakizaya people, hasEthnonymInJapanese, サキザヤ族]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEthnonymInJapanese Context triple: [Sakizaya people, hasEthnonymInJapanese, サキザヤ族]
-
A.
hasNameInJapanese
chosen
Indicates that an entity is associated with a specific name expressed in the Japanese language.
-
B.
eraNameInJapanese
Indicates the Japanese-language name used for a specific historical or calendar era.
-
C.
hasJapaneseSurname
Indicates that the person or entity possesses a surname that is of Japanese origin or is commonly used in Japanese naming conventions.
-
D.
hasOfficialNameInJapanese
Indicates that an entity has an official, formally recognized name expressed in the Japanese language.
-
E.
hasNameInKanji
Indicates that an entity is associated with a specific written form of its name in Kanji characters.
- 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_69e2c4cf54248190af7b0c2d9ade9830 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6ca751c8190a040c10d701ecf3a |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:30 a.m.