Triple
T22713055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Germans in Hungary |
E561651
|
entity |
| Predicate | notableSettlement |
P13187
|
FINISHED |
| Object | Mór |
—
|
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: Mór | Statement: [Germans in Hungary, notableSettlement, Mór]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mór Context triple: [Germans in Hungary, notableSettlement, Mór]
-
A.
Mór
chosen
Mór is a town in central Hungary known for its wine production and location between the Vértes and Bakony hills.
-
B.
Velkua
Velkua is a former island municipality in southwestern Finland known for its coastal archipelago landscape in the Baltic Sea.
-
C.
Bór
Bór is the wartime nickname of Tadeusz Bór-Komorowski, the Polish general who commanded the Home Army and led the Warsaw Uprising during World War II.
-
D.
Bór
Bór is a village in southern Poland located within the administrative district of Gmina Szaflary in Lesser Poland Voivodeship.
-
E.
Dainava
Dainava is a historical region in the territory of present-day Lithuania and northeastern Poland, traditionally associated with the Baltic Yotvingian and Lithuanian tribes.
- 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.