Triple
T10012492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baranya County |
E199407
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Harkány
Harkány is a Hungarian spa town in southern Transdanubia renowned for its medicinal thermal baths and health tourism.
|
E945088
|
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: Harkány | Statement: [Baranya County, containsTown, Harkány]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harkány Context triple: [Baranya County, containsTown, Harkány]
-
A.
Pécsvárad
Pécsvárad is a small historic town in southern Hungary known for its medieval abbey and scenic setting near the Mecsek Mountains.
-
B.
Nagyvázsony
Nagyvázsony is a village in Veszprém County, Hungary, known for its historic Kinizsi Castle and traditional rural character.
-
C.
Gyulafehérvár
Gyulafehérvár, known today as Alba Iulia in Romania, is a historic city that served as the political and cultural center of Transylvania for centuries.
-
D.
Törökbálint
Törökbálint is a town in Pest County, Hungary, located just southwest of Budapest and known as a suburban residential area with growing commercial and industrial zones.
-
E.
Csákvár
Csákvár is a small town in central Hungary known for its rural character and location within the Transdanubian region.
- 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: Harkány Triple: [Baranya County, containsTown, Harkány]
Generated description
Harkány is a Hungarian spa town in southern Transdanubia renowned for its medicinal thermal baths and health tourism.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Harkány Target entity description: Harkány is a Hungarian spa town in southern Transdanubia renowned for its medicinal thermal baths and health tourism.
-
A.
Pécsvárad
Pécsvárad is a small historic town in southern Hungary known for its medieval abbey and scenic setting near the Mecsek Mountains.
-
B.
Nagyvázsony
Nagyvázsony is a village in Veszprém County, Hungary, known for its historic Kinizsi Castle and traditional rural character.
-
C.
Gyulafehérvár
Gyulafehérvár, known today as Alba Iulia in Romania, is a historic city that served as the political and cultural center of Transylvania for centuries.
-
D.
Törökbálint
Törökbálint is a town in Pest County, Hungary, located just southwest of Budapest and known as a suburban residential area with growing commercial and industrial zones.
-
E.
Csákvár
Csákvár is a small town in central Hungary known for its rural character and location within the Transdanubian region.
- 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_69ca8315a1a08190ab310f25620f362b |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd3cf5b881908f5318e55bdd22b6 |
completed | April 2, 2026, 1:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f08ec96fe88190b791e6f50f39173f |
completed | April 28, 2026, 10:41 a.m. |
| NEDg | Description generation | batch_69f0bd36673881908530b68e496c3d2e |
completed | April 28, 2026, 1:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f0eec1f5d081908624fe2a93995fe5 |
completed | April 28, 2026, 5:30 p.m. |
Created at: March 30, 2026, 8:52 p.m.