Triple
T15142227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kiko |
E361711
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Akishino |
—
|
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: Akishino | Statement: [Kiko, familyName, Akishino]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Akishino Context triple: [Kiko, familyName, Akishino]
-
A.
Akishino
chosen
Akishino is the imperial family name of a branch of Japan’s monarchy, borne by members such as Prince Hisahito and his parents, Crown Prince Fumihito and Crown Princess Kiko.
-
B.
Akiruno
Akiruno is a city in western Tokyo, Japan, known for its natural scenery, including rivers, forests, and hiking areas.
-
C.
Minamiashigara
Minamiashigara is a city in Kanagawa Prefecture, Japan, known for its natural hot springs, mountainous scenery, and proximity to the Hakone area.
-
D.
Marunouchi
Marunouchi is a central Tokyo business district known for its concentration of corporate headquarters, upscale offices, and proximity to Tokyo Station and the Imperial Palace.
-
E.
Fukusaki
Fukusaki is a town in Hyōgo Prefecture, Japan, known for its rural setting and association with folklorist Kunio Yanagita.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d85a0759908190b8a051d2e2a1cbe6 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005c5c4248190b57234e3ccf2831b |
completed | April 15, 2026, 9:40 p.m. |
Created at: April 10, 2026, 3:07 a.m.