Triple
T18560055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donaueschingen |
E453611
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Vác |
—
|
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: Vác | Statement: [Donaueschingen, hasTwinTown, Vác]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vác Context triple: [Donaueschingen, hasTwinTown, Vác]
-
A.
Vác
chosen
Vác is a historic town on the Danube in northern Hungary, known for its Baroque architecture and role as a regional cultural and religious center.
-
B.
Nitra
Nitra is one of the oldest cities in Slovakia, known for its historic castle, early Christian heritage, and role as a cultural and academic center.
-
C.
Zvolen
Zvolen is a historic town in central Slovakia known for its medieval castle and role as a regional transport and cultural hub.
-
D.
Vsetín
Vsetín is a town in the eastern Czech Republic known as an industrial and cultural center of the Moravian Wallachia region.
-
E.
Vysočany
Vysočany is a district in the northeastern part of Prague, Czech Republic, known for its mix of residential areas, industrial heritage, and modern commercial development.
- 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_69d8d388b0c881908e610a1c45b52640 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e538098a148190b0fc7098ce3c62fd |
completed | April 19, 2026, 8:16 p.m. |
Created at: April 10, 2026, 11:42 a.m.