Triple
T20821436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Szatmár |
E512580
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object |
Nagybánya
Nagybánya, known today as Baia Mare, is a city in northwestern Romania recognized for its mining history and cultural heritage.
|
E1452261
|
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: Nagybánya | Statement: [Szatmár, hasTwinTown, Nagybánya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nagybánya Context triple: [Szatmár, hasTwinTown, Nagybánya]
-
A.
Besztercebánya
Besztercebánya is a historic mining and cultural city in central Slovakia, known in Hungarian as Besztercebánya and in Slovak as Banská Bystrica.
-
B.
Selmecbánya
Selmecbánya is the historical Hungarian name for Banská Štiavnica, a renowned medieval mining town and UNESCO World Heritage site in present-day central Slovakia.
-
C.
Kazincbarcika
Kazincbarcika is an industrial town in northeastern Hungary, located in Borsod-Abaúj-Zemplén County.
-
D.
Mátészalka
Mátészalka is a town in northeastern Hungary known as a local administrative and economic center within the Northern Great Plain region.
-
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: Nagybánya Triple: [Szatmár, hasTwinTown, Nagybánya]
Generated description
Nagybánya, known today as Baia Mare, is a city in northwestern Romania recognized for its mining history and cultural heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nagybánya Target entity description: Nagybánya, known today as Baia Mare, is a city in northwestern Romania recognized for its mining history and cultural heritage.
-
A.
Besztercebánya
Besztercebánya is a historic mining and cultural city in central Slovakia, known in Hungarian as Besztercebánya and in Slovak as Banská Bystrica.
-
B.
Selmecbánya
Selmecbánya is the historical Hungarian name for Banská Štiavnica, a renowned medieval mining town and UNESCO World Heritage site in present-day central Slovakia.
-
C.
Kazincbarcika
Kazincbarcika is an industrial town in northeastern Hungary, located in Borsod-Abaúj-Zemplén County.
-
D.
Mátészalka
Mátészalka is a town in northeastern Hungary known as a local administrative and economic center within the Northern Great Plain region.
-
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_69e0b4ce39108190a6e8e5df4f1c8dc5 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2f7a1548190b6ef3f1cfad37c1c |
completed | April 21, 2026, 12:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a090079c5688190a9ba9f6e8f69c64e |
completed | May 16, 2026, 11:40 p.m. |
| NEDg | Description generation | batch_6a090146ab948190a6c76f5c978b5268 |
completed | May 16, 2026, 11:44 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0902070ca081908e75dddcda808eea |
completed | May 16, 2026, 11:47 p.m. |
Created at: April 16, 2026, 12:41 p.m.