Triple
T20328085
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nitra River |
E492393
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Nitra |
—
|
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: Nitra | Statement: [Nitra River, flowsThrough, Nitra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nitra Context triple: [Nitra River, flowsThrough, Nitra]
-
A.
Nitra
chosen
Nitra is one of the oldest cities in Slovakia, known for its historic castle, early Christian heritage, and role as a cultural and academic center.
-
B.
Vác
Vác is a historic town on the Danube in northern Hungary, known for its Baroque architecture and role as a regional cultural and religious center.
-
C.
Vsetín
Vsetín is a town in the eastern Czech Republic known as an industrial and cultural center of the Moravian Wallachia region.
-
D.
Brdy
Brdy is a forested mountain range in the Central Bohemian Region of the Czech Republic, known for its rolling hills, former military areas, and extensive hiking and cycling trails.
-
E.
Karviná
Karviná is an industrial city in the Moravian-Silesian Region of the Czech Republic, historically part of Cieszyn Silesia and known for its coal mining heritage.
- 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_69e0b4a0134081909113563e1c3ba68a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e677e513608190b70527cd9f4d5da3 |
completed | April 20, 2026, 7 p.m. |
Created at: April 16, 2026, 11:21 a.m.