Triple
T19779947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mateusz |
E475103
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Matej |
—
|
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: Matej | Statement: [Mateusz, hasVariant, Matej]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matej Context triple: [Mateusz, hasVariant, Matej]
-
A.
Matej
chosen
Matej is a masculine given name commonly used in Slavic countries, equivalent to Matthew in English.
-
B.
Matúš
Matúš is the Slovak form of the given name Matthew, commonly used in Slovakia and other Slovak-speaking communities.
-
C.
Matyáš
Matyáš is the given name of Jindřich Matyáš Thurn, a notable Bohemian nobleman and military leader of the early 17th century.
-
D.
Jozef
Jozef is a masculine given name of Hebrew origin, commonly used in Central and Eastern Europe as a variant of Joseph.
-
E.
Juraj
Juraj is a Slavic given name, equivalent to the English name George.
- 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_69d8e51a43a08190956bc6df13c91a77 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65382ff308190832800dd60675f7a |
completed | April 20, 2026, 4:25 p.m. |
Created at: April 10, 2026, 1:49 p.m.