Triple
T21011641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uji tea |
E517563
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Uji City |
—
|
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: Uji City | Statement: [Uji tea, associatedWith, Uji City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Uji City Context triple: [Uji tea, associatedWith, Uji City]
-
A.
Uji City
chosen
Uji City is a historic city in Kyoto Prefecture, Japan, renowned for its high-quality green tea production and UNESCO-listed Byōdō-in Temple.
-
B.
Nanyo City
Nanyo City is a municipality in northeastern Japan known for its hot springs, fruit production, and scenic rural landscapes.
-
C.
Tendo City
Tendo City is a municipality in northeastern Japan known for its production of shogi (Japanese chess) pieces and hot spring resorts.
-
D.
Uji-shi
Uji-shi is a city in Kyoto Prefecture, Japan, renowned for its historic temples and high-quality green tea production.
-
E.
Toda City
Toda City is a municipality in Saitama Prefecture, Japan, located just north of Tokyo and known as a residential and commuter town within the Greater Tokyo metropolitan area.
- 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_69e0b50192308190a284fcc89dd23a49 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc40f91c81908c9b6d99869de7aa |
completed | April 21, 2026, 4:25 a.m. |
Created at: April 16, 2026, 1:53 p.m.