Triple
T19180807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toyokawa |
E469565
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Okazaki |
—
|
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: Okazaki | Statement: [Toyokawa, borders, Okazaki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Okazaki Context triple: [Toyokawa, borders, Okazaki]
-
A.
Okazaki
chosen
Okazaki is a historic city in central Japan known as the birthplace of shogun Tokugawa Ieyasu and for its well-preserved castle and traditional festivals.
-
B.
Okazaki area
The Okazaki area is a prominent cultural district in Kyoto known for its museums, shrines, and large public park spaces.
-
C.
Ozaki
Ozaki is a Japanese surname borne by various notable figures in politics, literature, and the arts.
-
D.
Kawaguchi
Kawaguchi is a major commuter city in the Greater Tokyo area of Japan, located just north of Tokyo in Saitama Prefecture.
-
E.
Kodaira
Kodaira is a suburban city in western Tokyo, Japan, known as a residential area with parks, schools, and convenient rail access to central Tokyo.
- 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_69d8dd09d5a081909ae43c286651ae5a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f61be86c81908710341262e911cd |
completed | April 20, 2026, 9:47 a.m. |
Created at: April 10, 2026, 12:07 p.m.