Triple
T10092831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diósgyőr Castle |
E215785
|
entity |
| Predicate | locatedInNeighborhood |
P40
|
FINISHED |
| Object |
Diósgyőr
Diósgyőr is a historic district of Miskolc in northeastern Hungary, best known for its medieval castle and surrounding cultural heritage.
|
E1006515
|
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: Diósgyőr | Statement: [Diósgyőr Castle, locatedInNeighborhood, Diósgyőr]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Diósgyőr Context triple: [Diósgyőr Castle, locatedInNeighborhood, Diósgyőr]
-
A.
Győr
Győr is a historic city in northwestern Hungary, known as an important regional cultural and economic center at the confluence of the Danube, Rába, and Rábca rivers.
-
B.
Gödöllő
Gödöllő is a Hungarian town near Budapest best known for its historic Royal Palace, one of the largest Baroque palaces in Hungary.
-
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.
Dunaújváros
Dunaújváros is an industrial city in central Hungary known for its steel production and post-war socialist urban planning.
-
E.
Dombóvár
Dombóvár is a town in southern Hungary known as an important local transport and economic center within Tolna 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: Diósgyőr Triple: [Diósgyőr Castle, locatedInNeighborhood, Diósgyőr]
Generated description
Diósgyőr is a historic district of Miskolc in northeastern Hungary, best known for its medieval castle and surrounding cultural heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Diósgyőr Target entity description: Diósgyőr is a historic district of Miskolc in northeastern Hungary, best known for its medieval castle and surrounding cultural heritage.
-
A.
Győr
Győr is a historic city in northwestern Hungary, known as an important regional cultural and economic center at the confluence of the Danube, Rába, and Rábca rivers.
-
B.
Gödöllő
Gödöllő is a Hungarian town near Budapest best known for its historic Royal Palace, one of the largest Baroque palaces in Hungary.
-
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.
Dunaújváros
Dunaújváros is an industrial city in central Hungary known for its steel production and post-war socialist urban planning.
-
E.
Dombóvár
Dombóvár is a town in southern Hungary known as an important local transport and economic center within Tolna 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_69ca83a4947c8190823a7495dc5d96ed |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd05c3c0c8190927580717429a4e5 |
completed | April 2, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69b76e0cc8190aa7303347e0183d4 |
completed | May 3, 2026, 12:48 a.m. |
| NEDg | Description generation | batch_69f69d48e6948190a13afe3b8943d877 |
completed | May 3, 2026, 12:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f69dfa2b8481908827025a28bfb056 |
completed | May 3, 2026, 12:59 a.m. |
Created at: March 30, 2026, 9:01 p.m.