Triple
T11703648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kráľovský Chlmec |
E278184
|
entity |
| Predicate | hasNameInHungarian |
P27628
|
FINISHED |
| Object |
Királyhelmec
Királyhelmec is a town in southeastern Slovakia, near the Hungarian border, known for its significant Hungarian-speaking population and historical ties to the former Kingdom of Hungary.
|
E941829
|
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: Királyhelmec | Statement: [Kráľovský Chlmec, hasNameInHungarian, Királyhelmec]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Királyhelmec Context triple: [Kráľovský Chlmec, hasNameInHungarian, Királyhelmec]
-
A.
Csákvár
Csákvár is a small town in central Hungary known for its rural character and location within the Transdanubian region.
-
B.
Count of Beszterce
Count of Beszterce was a noble title in the Kingdom of Hungary historically associated with the influential Hunyadi family.
-
C.
Várpalota
Várpalota is a town in western Hungary known for its historical castle and industrial heritage.
-
D.
Harkányi
Harkányi is a Hungarian surname associated with individuals such as Mici Mária Harkányi.
-
E.
Pilisvörösvár
Pilisvörösvár is a town in central Hungary known for its German minority heritage and proximity to Budapest.
- 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: Királyhelmec Triple: [Kráľovský Chlmec, hasNameInHungarian, Királyhelmec]
Generated description
Királyhelmec is a town in southeastern Slovakia, near the Hungarian border, known for its significant Hungarian-speaking population and historical ties to the former Kingdom of Hungary.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Királyhelmec Target entity description: Királyhelmec is a town in southeastern Slovakia, near the Hungarian border, known for its significant Hungarian-speaking population and historical ties to the former Kingdom of Hungary.
-
A.
Csákvár
Csákvár is a small town in central Hungary known for its rural character and location within the Transdanubian region.
-
B.
Count of Beszterce
Count of Beszterce was a noble title in the Kingdom of Hungary historically associated with the influential Hunyadi family.
-
C.
Várpalota
Várpalota is a town in western Hungary known for its historical castle and industrial heritage.
-
D.
Harkányi
Harkányi is a Hungarian surname associated with individuals such as Mici Mária Harkányi.
-
E.
Pilisvörösvár
Pilisvörösvár is a town in central Hungary known for its German minority heritage and proximity to Budapest.
- 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_69d6aaff2ce88190b4a1e4b341ad5377 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a49b1080819096593733ee48a187 |
completed | April 10, 2026, 7:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef83525ae081909ee6f3fbb5d37dd7 |
completed | April 27, 2026, 3:40 p.m. |
| NEDg | Description generation | batch_69ef9b673120819097b542bb9a8f8bdb |
completed | April 27, 2026, 5:22 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69efd683366881909dd9621e7c57d0be |
completed | April 27, 2026, 9:34 p.m. |
Created at: April 8, 2026, 9:40 p.m.