Triple
T26864805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rotes Kloster |
E676435
|
entity |
| Predicate | deutscherNameVon |
P22792
|
FINISHED |
| Object | Červený Kláštor |
—
|
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: Červený Kláštor | Statement: [Rotes Kloster, deutscherNameVon, Červený Kláštor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deutscherNameVon Context triple: [Rotes Kloster, deutscherNameVon, Červený Kláštor]
-
A.
nameInGerman
chosen
Indicates that an entity is known or referred to by a specific name in the German language.
-
B.
equivalentSurnameInGerman
Indicates that two surnames are equivalent to each other when translated into or represented in the German language.
-
C.
EuropeanNameVariant
Indicates that one name is a variant or alternative form of another name as used in a European language or cultural context.
-
D.
countryNameGerman
Indicates the German-language name used to refer to a given country.
-
E.
czechName
Indicates that an entity has a name in the Czech language, specifying the Czech-language form of its name.
- F. None of above.
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_69eee9ba94bc8190b44c5d4397d04ecd |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f61e96d45881909f2b93dfc522064f |
completed | May 2, 2026, 3:56 p.m. |
| PD | Predicate disambiguation | batch_69f611ad2eb48190ac1ed0090f13f7a9 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 5:28 a.m.