Triple
T14316359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | markrabě moravský |
E354965
|
entity |
| Predicate | jazykový původ |
P1754
|
FINISHED |
| Object | staročeský titul |
—
|
LITERAL 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: staročeský titul | Statement: [markrabě moravský, jazykový původ, staročeský titul]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: jazykový původ Context triple: [markrabě moravský, jazykový původ, staročeský titul]
-
A.
hasLanguageOfOrigin
chosen
Indicates that one entity has its origin or source in the language specified by another entity.
-
B.
hasLinguisticHeritage
Indicates that one entity possesses or is associated with the linguistic background, tradition, or ancestry of another entity.
-
C.
sourceLanguageMeaning
Indicates that one entity expresses the meaning or sense of another entity in a particular source language.
-
D.
indirectOriginLanguage
Indicates that something originates from a particular language, not directly but through one or more intermediate languages or sources.
-
E.
speciesOrigin
Indicates the place, environment, or source from which a species originally arose or evolved.
- 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_69d8278ed42c8190b9f882dcce611347 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8838e45c819080ee69dd39e3bd43 |
completed | April 14, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69de2a9515f4819081aabf251bca5878 |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:12 a.m.