Triple
T12977507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kinoshita Tōkichirō |
E321565
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Nene |
E158363
|
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: Nene | Statement: [Kinoshita Tōkichirō, spouse, Nene]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nene Context triple: [Kinoshita Tōkichirō, spouse, Nene]
-
A.
Nene
chosen
Nene was the principal wife of Japanese warlord Toyotomi Hideyoshi and a politically influential noblewoman during the late Sengoku period.
-
B.
Nene
Nene is a major river in eastern England that flows through Northamptonshire, Cambridgeshire, and Norfolk before reaching The Wash on the North Sea.
-
C.
Nenê
Nenê is a Brazilian professional basketball player and longtime NBA center known for his physical interior play and key contributions to both the Denver Nuggets and Washington Wizards.
-
D.
Nena
Nena is a German pop singer and actress best known internationally for her 1983 hit song "99 Luftballons."
-
E.
Nane
Nane is a Swedish lawyer and artist best known as the widow of former United Nations Secretary-General Kofi Annan.
- 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_69d80763bd6c819094437da5b20b01d2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e48c0208190bb7ec80780480b37 |
completed | April 10, 2026, 10:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6b8f0315c8190aae5908ba65d5867 |
completed | May 3, 2026, 2:54 a.m. |
Created at: April 9, 2026, 8:38 p.m.