Triple
T14147995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | District XI of Budapest |
E350602
|
entity |
| Predicate | hasNeighbourhood |
P4813
|
FINISHED |
| Object |
Kelenvölgy
Kelenvölgy is a primarily residential neighborhood in Budapest’s 11th District, known for its suburban character and green, quiet surroundings.
|
E1081664
|
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: Kelenvölgy | Statement: [District XI of Budapest, hasNeighbourhood, Kelenvölgy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kelenvölgy Context triple: [District XI of Budapest, hasNeighbourhood, Kelenvölgy]
-
A.
Kunhegyes
Kunhegyes is a small town in Jász-Nagykun-Szolnok County in central Hungary, known for its rural character and agricultural surroundings.
-
B.
Nagyerdő
Nagyerdő is a large, historic forested park and recreational area in Debrecen, Hungary, known for its natural beauty and cultural attractions.
-
C.
Gödöllő Hills
Gödöllő Hills is a hilly geographical region in central Hungary known for its rolling landscapes, forests, and proximity to Budapest.
-
D.
Kékes
Kékes is the highest peak in Hungary, known for its popular hiking trails and ski resort facilities.
-
E.
Lővérek Hills
Lővérek Hills is a forested hilly area near Sopron in western Hungary, known for its hiking trails, lookout towers, and recreational opportunities.
- 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: Kelenvölgy Triple: [District XI of Budapest, hasNeighbourhood, Kelenvölgy]
Generated description
Kelenvölgy is a primarily residential neighborhood in Budapest’s 11th District, known for its suburban character and green, quiet surroundings.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kelenvölgy Target entity description: Kelenvölgy is a primarily residential neighborhood in Budapest’s 11th District, known for its suburban character and green, quiet surroundings.
-
A.
Kunhegyes
Kunhegyes is a small town in Jász-Nagykun-Szolnok County in central Hungary, known for its rural character and agricultural surroundings.
-
B.
Nagyerdő
Nagyerdő is a large, historic forested park and recreational area in Debrecen, Hungary, known for its natural beauty and cultural attractions.
-
C.
Gödöllő Hills
Gödöllő Hills is a hilly geographical region in central Hungary known for its rolling landscapes, forests, and proximity to Budapest.
-
D.
Kékes
Kékes is the highest peak in Hungary, known for its popular hiking trails and ski resort facilities.
-
E.
Lővérek Hills
Lővérek Hills is a forested hilly area near Sopron in western Hungary, known for its hiking trails, lookout towers, and recreational opportunities.
- 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_69d827865f608190b311820428ae027b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61237ef481909374c1f68a2370b7 |
completed | April 14, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdf205c788190920b5055f9fe63a8 |
completed | May 7, 2026, 6:51 p.m. |
| NEDg | Description generation | batch_69fce266b2a08190998f04913064e43f |
completed | May 7, 2026, 7:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fce2cd8cb481908e3e5a421e732948 |
completed | May 7, 2026, 7:06 p.m. |
Created at: April 10, 2026, 12:55 a.m.