Triple
T22829207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karlsruhe district |
E565749
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Karlsbad |
—
|
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: Karlsbad | Statement: [Karlsruhe district, contains, Karlsbad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karlsbad Context triple: [Karlsruhe district, contains, Karlsbad]
-
A.
Karlsbad
Karlsbad is the German name for Karlovy Vary, a renowned spa town in the Czech Republic famous for its hot springs and historic architecture.
-
B.
Karlsbad
chosen
Karlsbad is a municipality in the district of Karlsruhe in the state of Baden-Württemberg in southwestern Germany.
-
C.
Mariánské Lázně
Mariánské Lázně is a renowned spa town in the western Czech Republic, famous for its numerous mineral springs, elegant 19th-century architecture, and therapeutic treatments.
-
D.
Klatovy
Klatovy is a historic town in the Czech Republic known for its well-preserved architecture, including Baroque churches and catacombs, and its role as a regional administrative center.
-
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_69e24585ab1c81909b2b5065d15805d5 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17e2a0e308190941064965346f890 |
completed | April 29, 2026, 3:42 a.m. |
Created at: April 17, 2026, 3:34 p.m.