Triple
T9703621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pest County |
E234839
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Nagykőrös
Nagykőrös is a historic town in central Hungary known for its agricultural traditions and small-town character.
|
E883253
|
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: Nagykőrös | Statement: [Pest County, hasSettlement, Nagykőrös]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nagykőrös Context triple: [Pest County, hasSettlement, Nagykőrös]
-
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.
Nagyvázsony
Nagyvázsony is a village in Veszprém County, Hungary, known for its historic Kinizsi Castle and traditional rural character.
-
C.
Gyöngyös
Gyöngyös is a historic town in northern Hungary known as a gateway to the Mátra mountain range and its surrounding wine-producing region.
-
D.
Tiszaújváros
Tiszaújváros is an industrial town in northeastern Hungary known for its large chemical and energy industries and its location along the Tisza River.
-
E.
Mezőkeresztes
Mezőkeresztes is a town in northeastern Hungary historically notable as the site of a major 1596 battle between Ottoman and Habsburg forces.
- 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: Nagykőrös Triple: [Pest County, hasSettlement, Nagykőrös]
Generated description
Nagykőrös is a historic town in central Hungary known for its agricultural traditions and small-town character.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nagykőrös Target entity description: Nagykőrös is a historic town in central Hungary known for its agricultural traditions and small-town character.
-
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.
Nagyvázsony
Nagyvázsony is a village in Veszprém County, Hungary, known for its historic Kinizsi Castle and traditional rural character.
-
C.
Gyöngyös
Gyöngyös is a historic town in northern Hungary known as a gateway to the Mátra mountain range and its surrounding wine-producing region.
-
D.
Tiszaújváros
Tiszaújváros is an industrial town in northeastern Hungary known for its large chemical and energy industries and its location along the Tisza River.
-
E.
Mezőkeresztes
Mezőkeresztes is a town in northeastern Hungary historically notable as the site of a major 1596 battle between Ottoman and Habsburg forces.
- 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_69ca84cc78808190a56f3402b7c139a7 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9d73a0148190ad4178fd462cdd9c |
completed | April 1, 2026, 10:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de21a949508190ad16b061ead5ed24 |
completed | April 14, 2026, 11:14 a.m. |
| NEDg | Description generation | batch_69de25d25474819081402b75ef7492f6 |
completed | April 14, 2026, 11:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69de2808244c8190bdb2d4d49f30e0d7 |
completed | April 14, 2026, 11:42 a.m. |
Created at: March 30, 2026, 8:18 p.m.