Triple
T20816002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tapolca District |
E512438
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Zalaszántó
Zalaszántó is a village in western Hungary known for its scenic rural setting near Lake Balaton and its large Buddhist stupa, one of the biggest in Europe.
|
E1462478
|
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: Zalaszántó | Statement: [Tapolca District, containsSettlement, Zalaszántó]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zalaszántó Context triple: [Tapolca District, containsSettlement, Zalaszántó]
-
A.
Nagykálló
Nagykálló is a town in northeastern Hungary known for its historical architecture and traditional cultural heritage.
-
B.
Egerszalók
Egerszalók is a Hungarian village famous for its thermal springs and striking terraced salt hill spa complex.
-
C.
Zalakomár
Zalakomár is a village in southwestern Hungary known for its rural character and proximity to the Zala River and nearby wetlands.
-
D.
Bonyhád
Bonyhád is a town in southern Hungary known as an important local center within Tolna County.
-
E.
Nagykőrös
Nagykőrös is a historic town in central Hungary known for its agricultural traditions and small-town character.
- 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: Zalaszántó Triple: [Tapolca District, containsSettlement, Zalaszántó]
Generated description
Zalaszántó is a village in western Hungary known for its scenic rural setting near Lake Balaton and its large Buddhist stupa, one of the biggest in Europe.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Zalaszántó Target entity description: Zalaszántó is a village in western Hungary known for its scenic rural setting near Lake Balaton and its large Buddhist stupa, one of the biggest in Europe.
-
A.
Nagykálló
Nagykálló is a town in northeastern Hungary known for its historical architecture and traditional cultural heritage.
-
B.
Egerszalók
Egerszalók is a Hungarian village famous for its thermal springs and striking terraced salt hill spa complex.
-
C.
Zalakomár
Zalakomár is a village in southwestern Hungary known for its rural character and proximity to the Zala River and nearby wetlands.
-
D.
Bonyhád
Bonyhád is a town in southern Hungary known as an important local center within Tolna County.
-
E.
Nagykőrös
Nagykőrös is a historic town in central Hungary known for its agricultural traditions and small-town character.
- 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_69e0b4cd25088190b48ca9700cd24efc |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2f3473c81908c43a2ec242b1acd |
completed | April 21, 2026, 12:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a093b3ea9bc8190a39b2ef56451db25 |
completed | May 17, 2026, 3:51 a.m. |
| NEDg | Description generation | batch_6a093d7436d48190ba38b0133ecc5fa5 |
completed | May 17, 2026, 4 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a093ddfc648819088243ef420140d2b |
completed | May 17, 2026, 4:02 a.m. |
Created at: April 16, 2026, 12:41 p.m.