Triple
T8722643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ústí nad Labem Region |
E207048
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Bílina |
E394627
|
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: Bílina | Statement: [Ústí nad Labem Region, containsCity, Bílina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bílina Context triple: [Ústí nad Labem Region, containsCity, Bílina]
-
A.
Bílina
chosen
Bílina is a river in the Czech Republic that flows through the Ústí nad Labem Region and is known for passing through several industrial and mining areas.
-
B.
Bóbrka
Bóbrka is a village in southeastern Poland historically significant as one of the birthplaces of the modern oil industry.
-
C.
Lučina
Lučina is a river in the Moravian-Silesian Region of the Czech Republic that flows through the city of Ostrava.
-
D.
Jilava
Jilava is a locality in Romania best known for its historic prison and fortress, which were used for political detentions and executions, especially during the 20th century.
-
E.
Běloves
Běloves is a district or locality within the town of Náchod in the Hradec Králové 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_69ca835811d8819081ea00fd2a2c9a1c |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d0609f48190adc56226724b16c6 |
completed | March 31, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf290001108190a90784b13a0a25b1 |
completed | April 3, 2026, 2:42 a.m. |
Created at: March 30, 2026, 6:36 p.m.