Triple
T10012486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baranya County |
E199407
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object | Komló |
E164474
|
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: Komló | Statement: [Baranya County, containsTown, Komló]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Komló Context triple: [Baranya County, containsTown, Komló]
-
A.
Komló
chosen
Komló is a town in southern Hungary known historically for its coal mining and hop-growing industries.
-
B.
Törökbálint
Törökbálint is a town in Pest County, Hungary, located just southwest of Budapest and known as a suburban residential area with growing commercial and industrial zones.
-
C.
Mátészalka
Mátészalka is a town in northeastern Hungary known as a local administrative and economic center within the Northern Great Plain region.
-
D.
Százhalombatta
Százhalombatta is a Hungarian town on the Danube known for its major oil refinery and significant archaeological heritage, including Bronze Age burial mounds.
-
E.
Kalocsa
Kalocsa is a historic town in southern Hungary known as an important Roman Catholic archiepiscopal center and for its traditional paprika production and folk art.
- 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_69ca8315a1a08190ab310f25620f362b |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd3cf5b881908f5318e55bdd22b6 |
completed | April 2, 2026, 1:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef8185c6e08190949020a80c24f2b8 |
completed | April 27, 2026, 3:32 p.m. |
Created at: March 30, 2026, 8:52 p.m.