Triple
T22713056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Germans in Hungary |
E561651
|
entity |
| Predicate | notableSettlement |
P13187
|
FINISHED |
| Object | Budaörs |
—
|
NE NERFINISHED |
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: Budaörs | Statement: [Germans in Hungary, notableSettlement, Budaörs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Budaörs Context triple: [Germans in Hungary, notableSettlement, Budaörs]
-
A.
Budaörs
chosen
Budaörs is a suburban town near Budapest in Hungary, known for its rapid post-communist development and role as a commercial and residential hub.
-
B.
Gödöllő
Gödöllő is a Hungarian town near Budapest best known for its historic Royal Palace, one of the largest Baroque palaces in Hungary.
-
C.
Kispest
Kispest is a district in Budapest, Hungary, known as a largely residential area with its own local commercial centers and transport connections.
-
D.
Kaposvár
Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy County.
-
E.
Budakeszi
Budakeszi is a small town in Hungary, located just west of Budapest and known for its surrounding forests and natural recreational areas.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2454f1348819088d83f420925a5c1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1790ab6208190a342f076002324ab |
completed | April 29, 2026, 3:20 a.m. |
Created at: April 17, 2026, 3:18 p.m.