Triple
T14059807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nógrád County |
E338312
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Szécsény
Szécsény is a historic town in northern Hungary known for its medieval architecture and role as a regional center in Nógrád County.
|
E1157584
|
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: Szécsény | Statement: [Nógrád County, containsSettlement, Szécsény]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Szécsény Context triple: [Nógrád County, containsSettlement, Szécsény]
-
A.
Kőszeg
Kőszeg is a historic Hungarian town near the Austrian border, renowned for its well-preserved medieval architecture and role in defending against Ottoman sieges.
-
B.
Nagykőrös
Nagykőrös is a historic town in central Hungary known for its agricultural traditions and small-town character.
-
C.
Füzesabony
Füzesabony is a small town in northeastern Hungary known as a regional railway junction and gateway to the Bükk and Mátra regions.
-
D.
Nagyvázsony
Nagyvázsony is a village in Veszprém County, Hungary, known for its historic Kinizsi Castle and traditional rural character.
-
E.
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.
- 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: Szécsény Triple: [Nógrád County, containsSettlement, Szécsény]
Generated description
Szécsény is a historic town in northern Hungary known for its medieval architecture and role as a regional center in Nógrád County.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Szécsény Target entity description: Szécsény is a historic town in northern Hungary known for its medieval architecture and role as a regional center in Nógrád County.
-
A.
Kőszeg
Kőszeg is a historic Hungarian town near the Austrian border, renowned for its well-preserved medieval architecture and role in defending against Ottoman sieges.
-
B.
Nagykőrös
Nagykőrös is a historic town in central Hungary known for its agricultural traditions and small-town character.
-
C.
Füzesabony
Füzesabony is a small town in northeastern Hungary known as a regional railway junction and gateway to the Bükk and Mátra regions.
-
D.
Nagyvázsony
Nagyvázsony is a village in Veszprém County, Hungary, known for its historic Kinizsi Castle and traditional rural character.
-
E.
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.
- 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5686f51c81908c33143ecbaae83d |
completed | April 14, 2026, 3 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff218b93d48190a7e16c3934828aa8 |
completed | May 9, 2026, 11:59 a.m. |
| NEDg | Description generation | batch_69ff227b0060819092a08c897719849c |
completed | May 9, 2026, 12:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff238c841c8190b1a88aeb8c428cbc |
completed | May 9, 2026, 12:07 p.m. |
Created at: April 9, 2026, 10:21 p.m.