Triple
T21382962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gifu Prefecture |
E527409
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Tajimi |
—
|
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: Tajimi | Statement: [Gifu Prefecture, hasCity, Tajimi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tajimi Context triple: [Gifu Prefecture, hasCity, Tajimi]
-
A.
Tajimi
chosen
Tajimi is a city in Gifu Prefecture, Japan, known for its long tradition of ceramic production and pottery.
-
B.
Shikaoi
Shikaoi is a rural town in Hokkaido, Japan, known for its natural scenery, agriculture, and access to outdoor activities such as hiking and hot springs.
-
C.
Taketomi
Taketomi is a town in Okinawa Prefecture, Japan, encompassing several Yaeyama Islands and known for its traditional Ryukyuan village scenery and preserved cultural heritage.
-
D.
Daito
Daito is a skilled Japanese gunter and close ally of Aech in Ernest Cline’s science fiction novel "Ready Player One."
-
E.
Kazegaura
Kazegaura is a tranquil, wind-swept lakeside town in the visual novel "If My Heart Had Wings," known for its scenic vistas and serene atmosphere.
- 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_69e0b51f363c8190944000ab5523b02b |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b0f05278819096c511035ffc9777 |
completed | April 22, 2026, 11:28 a.m. |
Created at: April 16, 2026, 5:12 p.m.