Triple
T14615142
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mátraháza |
E343064
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Kékestető |
E338310
|
NE FINISHED |
How this triple was built (2 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: Kékestető | Statement: [Mátraháza, locatedNear, Kékestető]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kékestető Context triple: [Mátraháza, locatedNear, Kékestető]
-
A.
Kékes
chosen
Kékes is the highest peak in Hungary, known for its popular hiking trails and ski resort facilities.
-
B.
Tótkomlós
Tótkomlós is a small town in southeastern Hungary known for its agricultural surroundings and traditional rural character.
-
C.
Bicske
Bicske is a small town in central Hungary known for its historical significance and location along major transportation routes west of Budapest.
-
D.
Egri Bikavér
Egri Bikavér is a historic Hungarian red wine blend, often called “Bull’s Blood,” renowned for its robust, spicy character and association with the Eger wine region.
-
E.
Etelköz
Etelköz was the historical region in Eastern Europe where the migrating Magyars settled before conquering the Carpathian Basin.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d822dec68081908c2553145c4051dc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb45264988190a1df13e8b54a85bd |
completed | April 14, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fda922f29c8190af98a8241d86f7cd |
completed | May 8, 2026, 9:13 a.m. |
Created at: April 10, 2026, 1:25 a.m.