Triple
T9629139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shinzo Abe |
E232549
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Akie Abe |
E149041
|
NE 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: Akie Abe | Statement: [Shinzo Abe, spouse, Akie Abe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Akie Abe Context triple: [Shinzo Abe, spouse, Akie Abe]
-
A.
Akie Abe
chosen
Akie Abe is a Japanese radio DJ and socialite best known as the widow of former Prime Minister Shinzo Abe and for her outspoken, sometimes independent political views.
-
B.
Akiko Takeshita
Akiko Takeshita is a Japanese actress known internationally for her supporting role in the film "Lost in Translation."
-
C.
Naoko Takeshita
Naoko Takeshita was the wife of former Japanese Prime Minister Noboru Takeshita and a member of a prominent political family in Japan.
-
D.
Nobuko Abe
Nobuko Abe is a Japanese woman best known as the sister of former Prime Minister Taro Aso.
-
E.
Tanaka Makiko
Tanaka Makiko is a Japanese politician and former foreign minister known for her reformist stance and outspoken criticism of Japan’s political establishment.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca848793ec8190a93a12383a754dc0 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9b00162481908f396f6b6e470d6c |
completed | April 1, 2026, 10:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d182291c34819099f3f43769849c5d |
completed | April 4, 2026, 9:27 p.m. |
Created at: March 30, 2026, 8:10 p.m.