Triple
T9498585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weiden in der Oberpfalz |
E229075
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Matsubara |
E10795
|
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: Matsubara | Statement: [Weiden in der Oberpfalz, hasTwinTown, Matsubara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matsubara Context triple: [Weiden in der Oberpfalz, hasTwinTown, Matsubara]
-
A.
Matsubara
chosen
Matsubara is a suburban city in Japan’s Kansai region, located within Osaka Prefecture and forming part of the Osaka metropolitan area.
-
B.
Matsuda
Matsuda is a small town in Kanagawa Prefecture, Japan, known for its scenic views of Mount Fuji and seasonal flower festivals.
-
C.
Kamiyama
Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
-
D.
Hiranaka
Hiranaka is a Japanese surname borne by individuals such as former professional boxer Akinobu Hiranaka.
-
E.
Marunouchi
Marunouchi is a central Tokyo business district known for its concentration of corporate headquarters, upscale offices, and proximity to Tokyo Station and the Imperial Palace.
- 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_69ca84753660819098e8d416e89e26ae |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd95ef06b88190b7a840caddea3e38 |
completed | April 1, 2026, 10:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e2d62cce008190ae269bbd289625a0 |
completed | April 18, 2026, 12:54 a.m. |
Created at: March 30, 2026, 7:56 p.m.