Triple
T10939733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kagawa Prefecture |
E258435
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Marugame |
E783190
|
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: Marugame | Statement: [Kagawa Prefecture, hasCity, Marugame]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marugame Context triple: [Kagawa Prefecture, hasCity, Marugame]
-
A.
Marugame
chosen
Marugame is a coastal city in Japan’s Kagawa Prefecture, known for Marugame Castle and its traditional uchiwa (paper fans) craftsmanship.
-
B.
Semboku
Semboku is a city in Akita Prefecture, Japan, known for its historic samurai district in Kakunodate and scenic Lake Tazawa.
-
C.
Izumisano
Izumisano is a coastal city in Osaka Prefecture, Japan, known as the mainland gateway to Kansai International Airport and a hub for regional commerce and travel.
-
D.
Goshogawara
Goshogawara is a city in northern Japan known for its traditional Tachineputa Festival featuring towering illuminated floats.
-
E.
Kusatsu
Kusatsu is a Japanese city in Shiga Prefecture known as a regional commercial hub and transportation crossroads near Lake Biwa.
- 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_69d6aa8769b4819082bfe5e61b9017f0 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770c1389881909341170984211810 |
completed | April 9, 2026, 9:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feb7ca3e348190a75c1dd8aec73a40 |
completed | May 9, 2026, 4:27 a.m. |
Created at: April 8, 2026, 9:23 p.m.