Triple
T10309588
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hajdú-Bihar County |
E241851
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Nádudvar
Nádudvar is a town in eastern Hungary known for its agricultural traditions and location within the Northern Great Plain region.
|
E994112
|
NE FINISHED |
How this triple was built (4 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: Nádudvar | Statement: [Hajdú-Bihar County, containsCity, Nádudvar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nádudvar Context triple: [Hajdú-Bihar County, containsCity, Nádudvar]
-
A.
Dombóvár
Dombóvár is a town in southern Hungary known as an important local transport and economic center within Tolna County.
-
B.
Tiszaújváros
Tiszaújváros is an industrial town in northeastern Hungary known for its large chemical and energy industries and its location along the Tisza River.
-
C.
Dunakeszi
Dunakeszi is a town in Hungary located just north of Budapest, known as a rapidly growing suburban and commuter settlement along the Danube in Pest County.
-
D.
Nagyvázsony
Nagyvázsony is a village in Veszprém County, Hungary, known for its historic Kinizsi Castle and traditional rural character.
-
E.
Kalocsa
Kalocsa is a historic town in southern Hungary known as an important Roman Catholic archiepiscopal center and for its traditional paprika production and folk art.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Nádudvar Triple: [Hajdú-Bihar County, containsCity, Nádudvar]
Generated description
Nádudvar is a town in eastern Hungary known for its agricultural traditions and location within the Northern Great Plain region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nádudvar Target entity description: Nádudvar is a town in eastern Hungary known for its agricultural traditions and location within the Northern Great Plain region.
-
A.
Dombóvár
Dombóvár is a town in southern Hungary known as an important local transport and economic center within Tolna County.
-
B.
Tiszaújváros
Tiszaújváros is an industrial town in northeastern Hungary known for its large chemical and energy industries and its location along the Tisza River.
-
C.
Dunakeszi
Dunakeszi is a town in Hungary located just north of Budapest, known as a rapidly growing suburban and commuter settlement along the Danube in Pest County.
-
D.
Nagyvázsony
Nagyvázsony is a village in Veszprém County, Hungary, known for its historic Kinizsi Castle and traditional rural character.
-
E.
Kalocsa
Kalocsa is a historic town in southern Hungary known as an important Roman Catholic archiepiscopal center and for its traditional paprika production and folk art.
- F. None of above. chosen
Provenance (5 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_69d381ac38808190a8ca7457c85b625b |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d32a18ac81909b4efd8c1ba3e113 |
completed | April 7, 2026, 9:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6684574908190bd7e3d1a7dd6d876 |
completed | May 2, 2026, 9:10 p.m. |
| NEDg | Description generation | batch_69f669527fe881909baeb84ccff506c8 |
completed | May 2, 2026, 9:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f669fe4bc48190adba50ad58b10c45 |
completed | May 2, 2026, 9:17 p.m. |
Created at: April 6, 2026, 11:47 a.m.