Triple
T12238963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jizera River |
E291676
|
entity |
| Predicate | confluenceLocation |
P3421
|
FINISHED |
| Object | Mělník |
E231915
|
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: Mělník | Statement: [Jizera River, confluenceLocation, Mělník]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mělník Context triple: [Jizera River, confluenceLocation, Mělník]
-
A.
Mělník
chosen
Mělník is a historic Czech town north of Prague, known for its wine production and its location at the confluence of the Elbe and Vltava rivers.
-
B.
Měčín
Měčín is a small town in the Plzeň Region of the Czech Republic.
-
C.
Osek
Osek is a town in the Czech Republic historically associated with the family origins of writer Franz Kafka’s father, Hermann Kafka.
-
D.
Třeboň
Třeboň is a historic spa town in the Czech Republic renowned for its Renaissance architecture, fishpond landscapes, and long tradition of carp farming.
-
E.
Broumov
Broumov is a historic town in northeastern Bohemia, Czech Republic, known for its Benedictine monastery and proximity to the Broumov Walls sandstone rock formations.
- 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_69d6ab67950c8190be08450a06228c4b |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91cb45340819093365f8efdf85f75 |
completed | April 10, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f739668f3481909cc7564c3ede2896 |
completed | May 3, 2026, 12:02 p.m. |
Created at: April 8, 2026, 9:51 p.m.