Triple
T13367264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Forest, Belgium |
E318970
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Dunaújváros, Hungary |
E234840
|
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: Dunaújváros, Hungary | Statement: [Forest, Belgium, hasTwinTown, Dunaújváros, Hungary]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dunaújváros, Hungary Context triple: [Forest, Belgium, hasTwinTown, Dunaújváros, Hungary]
-
A.
Dunaújváros
chosen
Dunaújváros is an industrial city in central Hungary known for its steel production and post-war socialist urban planning.
-
B.
Kisvárda, Hungary
Kisvárda is a small town in northeastern Hungary known for its historic castle, thermal baths, and role as a regional cultural and economic center.
-
C.
Kaposvár, Hungary
Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy County.
-
D.
Budaörs, Hungary
Budaörs is a suburban town just west of Budapest in Hungary, known for its rapid post-communist development, commercial centers, and role as a key transport hub near the capital.
-
E.
Csákánydoroszló, Hungary
Csákánydoroszló is a small village in western Hungary, known as the birthplace of screenwriter and author Joe Eszterhas.
- 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_69d806b7bbac8190b85278c87fa7aff3 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dadcd652d48190a782fd1f57f34b6a |
completed | April 11, 2026, 11:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f72680df088190b8dbcc8ad0d7366e |
completed | May 3, 2026, 10:42 a.m. |
Created at: April 9, 2026, 9:32 p.m.