Triple
T14972903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yanaka |
E373367
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Kanto region |
E54245
|
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: Kanto region | Statement: [Yanaka, region, Kanto region]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kanto region Context triple: [Yanaka, region, Kanto region]
-
A.
Kanto
Kanto is a major geographical and metropolitan region of eastern Japan that includes Tokyo and several surrounding prefectures.
-
B.
Kanto Plain
The Kanto Plain is Japan's largest and most populous lowland region, encompassing Tokyo and surrounding urban and agricultural areas on central Honshu.
-
C.
Chubu region of Japan
The Chubu region of Japan is a central area on Japan’s main island of Honshu, encompassing diverse landscapes from the Japanese Alps to coastal plains and including major cities such as Nagoya.
-
D.
Jetisu Region
Jetisu Region is an administrative region in southeastern Kazakhstan known for its mountainous landscapes and historical role as part of the larger Almaty area.
-
E.
Kantō region
chosen
The Kantō region is a major geographical and economic area of eastern Honshu, Japan, encompassing Tokyo and several surrounding prefectures and serving as the country’s political and population center.
- 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_69d85ccbbcd48190acb56e7cf104d8ad |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6e767608190940eb6f16ea97451 |
completed | April 15, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe8be8af688190832efb00695f8b20 |
completed | May 9, 2026, 1:20 a.m. |
Created at: April 10, 2026, 2:50 a.m.