Triple
T10442161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fichtel Mountains |
E246194
|
entity |
| Predicate | sourceOfRiver |
P25636
|
FINISHED |
| Object | Eger (Ohře) |
E754423
|
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: Eger (Ohře) | Statement: [Fichtel Mountains, sourceOfRiver, Eger (Ohře)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eger (Ohře) Context triple: [Fichtel Mountains, sourceOfRiver, Eger (Ohře)]
-
A.
Eger
Eger is a historic city in northern Hungary known for its baroque architecture, castle, and wine culture.
-
B.
Eger
chosen
Eger is the former German name for the Czech town of Cheb, a historic settlement near the German border in western Bohemia.
-
C.
Přerov
Přerov is a city in the Olomouc Region of the Czech Republic, known as an important industrial and transport hub on the Bečva River.
-
D.
Orlice
Orlice is a river in the Czech Republic that flows through the city of Hradec Králové and is a tributary of the Labe (Elbe) River.
-
E.
Vsetín
Vsetín is a town in the eastern Czech Republic known as an industrial and cultural center of the Moravian Wallachia region.
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fb9ebf488190ae776bd65e94cb00 |
completed | April 7, 2026, 12:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87ee0c2208190ae8d51a2a89a2586 |
completed | April 10, 2026, 4:38 a.m. |
Created at: April 6, 2026, 12:15 p.m.