Triple
T4592622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yuriko Kikuchi |
E103530
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Kikuchi |
E140627
|
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: Kikuchi | Statement: [Yuriko Kikuchi, familyName, Kikuchi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kikuchi Context triple: [Yuriko Kikuchi, familyName, Kikuchi]
-
A.
Kikuchi
chosen
Kikuchi is a Japanese surname borne by various notable individuals across fields such as acting, sports, and academia.
-
B.
Ishkashimi
Ishkashimi is a lesser-known Eastern Iranian language spoken by small communities in parts of Afghanistan and Tajikistan.
-
C.
Kyotanabe
Kyotanabe is a city in Kyoto Prefecture, Japan, known for its residential suburbs, educational institutions, and location within the Kansai region.
-
D.
Kamiyama
Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
-
E.
Kasukabe
Kasukabe is a city in Japan known for its suburban character within the Greater Tokyo area and as the setting of the popular manga and anime series "Crayon Shin-chan."
- 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_69bd43dccaf08190aa89e9991a289719 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd592520ec8190b1bd4cb4d9b94c94 |
completed | March 20, 2026, 2:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bfdeaa224c8190a115d8af390eea71 |
completed | March 22, 2026, 12:20 p.m. |
Created at: March 20, 2026, 1:11 p.m.