Triple
T24547816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akie Abe |
E607273
|
entity |
| Predicate | spouseNameInJapanese |
P156276
|
FINISHED |
| Object | 安倍 晋三 |
—
|
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: 安倍 晋三 | Statement: [Akie Abe, spouseNameInJapanese, 安倍 晋三]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseNameInJapanese Context triple: [Akie Abe, spouseNameInJapanese, 安倍 晋三]
-
A.
spouseNameInKorean
Indicates that the predicate specifies the name of a person's spouse written in the Korean language.
-
B.
spouse name
Indicates that one entity is the legally recognized husband or wife of the other, specifying the partner’s name in a marital relationship.
-
C.
spouseNameInVietnamese
Indicates that the predicate specifies the name of a person's spouse as written or expressed in the Vietnamese language.
-
D.
spouseNameInPinyin
Indicates that it specifies the spouse’s name written in Pinyin (the Romanized form of Chinese characters).
-
E.
spouseFamilyName
Indicates that the object is the family name (surname) shared by or associated with a person's spouse.
- 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_69e2c4c9bf94819082d05da6f5c29907 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a8cb6dc081909bf37123d82ed2c9 |
completed | April 30, 2026, 12:56 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b99e7c8190ba7e2dc8729a314a |
completed | April 30, 2026, 12:47 a.m. |
| PDg | Predicate description generation | batch_69f2a846c5bc81909ba50cee483bea91 |
completed | April 30, 2026, 12:54 a.m. |
Created at: April 18, 2026, 2:27 a.m.