Martin Karafiát
E906314
Martin Karafiát is a researcher in speech and language processing, known for his contributions to automatic speech recognition and related computational linguistics work.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Martin Karafiát canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T11108947 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Martin Karafiát Context triple: [Tomas Mikolov, coAuthor, Martin Karafiát]
-
A.
Vlado Meller
Vlado Meller is a renowned audio mastering engineer known for his work on numerous high-profile albums across rock, pop, and hip-hop.
-
B.
Eduard Nápravník
Eduard Nápravník was a prominent 19th-century Czech-born conductor and composer who became a leading figure at the Imperial Mariinsky Theatre in St. Petersburg, championing Russian opera and symphonic music.
-
C.
Martin Bareš
Martin Bareš is a Czech neurologist and academic who serves as the rector of Masaryk University in Brno.
-
D.
Martin Rázus
Martin Rázus was a prominent Slovak Lutheran pastor, writer, and politician who became a leading figure in the Slovak national and autonomist movement in the early 20th century.
-
E.
Josef Baxa
Josef Baxa is a Czech lawyer and judge who serves as the President of the Constitutional Court of the Czech Republic and is known for his significant influence on the country’s judicial system.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Martin Karafiát Target entity description: Martin Karafiát is a researcher in speech and language processing, known for his contributions to automatic speech recognition and related computational linguistics work.
-
A.
Vlado Meller
Vlado Meller is a renowned audio mastering engineer known for his work on numerous high-profile albums across rock, pop, and hip-hop.
-
B.
Eduard Nápravník
Eduard Nápravník was a prominent 19th-century Czech-born conductor and composer who became a leading figure at the Imperial Mariinsky Theatre in St. Petersburg, championing Russian opera and symphonic music.
-
C.
Martin Bareš
Martin Bareš is a Czech neurologist and academic who serves as the rector of Masaryk University in Brno.
-
D.
Martin Rázus
Martin Rázus was a prominent Slovak Lutheran pastor, writer, and politician who became a leading figure in the Slovak national and autonomist movement in the early 20th century.
-
E.
Josef Baxa
Josef Baxa is a Czech lawyer and judge who serves as the President of the Constitutional Court of the Czech Republic and is known for his significant influence on the country’s judicial system.
- F. None of above. chosen
Statements (10)
| Predicate | Object |
|---|---|
| instanceOf |
person
ⓘ
researcher ⓘ |
| fieldOfWork |
automatic speech recognition
ⓘ
computational linguistics ⓘ speech processing ⓘ spoken language processing ⓘ |
| knownFor |
automatic speech recognition research
ⓘ
speech and language processing ⓘ |
| occupation |
researcher
ⓘ
scientist ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Martin Karafiát Description of subject: Martin Karafiát is a researcher in speech and language processing, known for his contributions to automatic speech recognition and related computational linguistics work.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.