Triple
T14756220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trenčín Region |
E346735
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object | Prievidza |
E300711
|
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: Prievidza | Statement: [Trenčín Region, containsTown, Prievidza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Prievidza Context triple: [Trenčín Region, containsTown, Prievidza]
-
A.
Prievidza
chosen
Prievidza is a historic town in central Slovakia known for its proximity to the spa town Bojnice and its role as a regional economic and cultural center.
-
B.
Prieska
Prieska is a small town in South Africa’s Northern Cape province, situated on the banks of the Orange River and serving as a regional agricultural and transport hub.
-
C.
Považie
Považie is a historical and geographical region of Slovakia situated along the Váh River, known for its valleys, towns, and cultural significance.
-
D.
Pravonín
Pravonín is a small municipality and village in the Central Bohemian Region of the Czech Republic.
-
E.
Předenice
Předenice is a small municipality and village located in the Plzeň Region of the Czech Republic.
- 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_69d822e8896c819091169882f9b20486 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7ef0fd48190bd4a8af128ef274c |
completed | April 14, 2026, 11:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdfb9e1b8481909abea3daabe91302 |
completed | May 8, 2026, 3:05 p.m. |
Created at: April 10, 2026, 1:30 a.m.