Triple
T14865793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angyalföld |
E349611
|
entity |
| Predicate | hasNotableSquare |
P7888
|
FINISHED |
| Object |
Lehel tér
Lehel tér is a major square and transport hub in Budapest, known for its busy metro station, market hall, and commercial activity.
|
E1123523
|
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: Lehel tér | Statement: [Angyalföld, hasNotableSquare, Lehel tér]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lehel tér Context triple: [Angyalföld, hasNotableSquare, Lehel tér]
-
A.
Lehel
Lehel is a historic and upscale central district of Munich, Germany, known for its elegant architecture and proximity to the Old Town and the Isar River.
-
B.
Népliget area
The Népliget area is a large public park and transport hub in Budapest, Hungary, known for its green spaces, sports facilities, and major international bus station.
-
C.
Parádfürdő
Parádfürdő is a spa village in northern Hungary known for its mineral springs and scenic location within the Mátra mountain region.
-
D.
Bonyhád
Bonyhád is a town in southern Hungary known as an important local center within Tolna County.
-
E.
Hollókő
Hollókő is a UNESCO World Heritage-listed Hungarian village renowned for its well-preserved traditional Palóc architecture and living rural culture.
- 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: Lehel tér Triple: [Angyalföld, hasNotableSquare, Lehel tér]
Generated description
Lehel tér is a major square and transport hub in Budapest, known for its busy metro station, market hall, and commercial activity.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lehel tér Target entity description: Lehel tér is a major square and transport hub in Budapest, known for its busy metro station, market hall, and commercial activity.
-
A.
Lehel
Lehel is a historic and upscale central district of Munich, Germany, known for its elegant architecture and proximity to the Old Town and the Isar River.
-
B.
Népliget area
The Népliget area is a large public park and transport hub in Budapest, Hungary, known for its green spaces, sports facilities, and major international bus station.
-
C.
Parádfürdő
Parádfürdő is a spa village in northern Hungary known for its mineral springs and scenic location within the Mátra mountain region.
-
D.
Bonyhád
Bonyhád is a town in southern Hungary known as an important local center within Tolna County.
-
E.
Hollókő
Hollókő is a UNESCO World Heritage-listed Hungarian village renowned for its well-preserved traditional Palóc architecture and living rural culture.
- 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_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded5761c688190b4477cb081554b51 |
completed | April 15, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe650e8aec8190acd4a9cb9cad2039 |
completed | May 8, 2026, 10:34 p.m. |
| NEDg | Description generation | batch_69fe65ac6a5c81908621dc17edc6b04f |
completed | May 8, 2026, 10:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe6697fe3881908aae42abe56d86f8 |
completed | May 8, 2026, 10:41 p.m. |
Created at: April 10, 2026, 1:55 a.m.