Triple
T19016754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JR-Q17 |
E465370
|
entity |
| Predicate | locatedInCity |
P40
|
FINISHED |
| Object | Osaka |
—
|
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: Osaka | Statement: [JR-Q17, locatedInCity, Osaka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Osaka Context triple: [JR-Q17, locatedInCity, Osaka]
-
A.
Osaka
chosen
Osaka is Japan's third-largest city and a major economic, cultural, and historical hub known for its vibrant street food, bustling nightlife, and role as a commercial center in the Kansai region.
-
B.
Nagoya
Nagoya is a major industrial and commercial city in central Japan, known as a manufacturing hub and the capital of Aichi Prefecture.
-
C.
Settsu, Osaka
Settsu, Osaka is a suburban city in northern Osaka Prefecture, Japan, known for its residential neighborhoods and convenient access to the Osaka metropolitan area.
-
D.
Higashiōsaka
Higashiōsaka is an industrial and residential city in Japan known for its manufacturing base and location within the Osaka metropolitan area.
-
E.
Nankoku City
Nankoku City is a regional city on the island of Shikoku in Japan, known for its agricultural production and proximity to the city of Kōchi.
- 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_69d8dd025c188190a1d81f5b4ec7e2c6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d6dc0f9081909cddc5186603e885 |
completed | April 20, 2026, 7:33 a.m. |
Created at: April 10, 2026, 12:02 p.m.