Triple
T16761758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paar |
E407359
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Karel Paar
Karel Paar is a notable individual who shares the surname Paar and is recognized for his distinct personal achievements.
|
E1242352
|
NE FINISHED |
How this triple was built (4 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: Karel Paar | Statement: [Paar, hasNotableBearer, Karel Paar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karel Paar Context triple: [Paar, hasNotableBearer, Karel Paar]
-
A.
Karel Hermánek
Karel Hermánek is a Czech actor known for his work in film, television, and theater, including a role in the 1993 war drama "Stalingrad."
-
B.
Josef Šebek
Josef Šebek is an actor known for appearing in the classic Czech New Wave film "A Blonde in Love."
-
C.
Karel Farský
Karel Farský was a Czech Catholic priest and theologian best known as the founder and first patriarch of the Czechoslovak Hussite Church in the early 20th century.
-
D.
Karel Šimka
Karel Šimka is a Czech lawyer and judge who serves as the president of the Supreme Administrative Court of the Czech Republic.
-
E.
Karel Klapálek
Karel Klapálek was a prominent Czechoslovak general and World War II resistance figure who played a key role in leading Czechoslovak forces on the Eastern Front.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Karel Paar Triple: [Paar, hasNotableBearer, Karel Paar]
Generated description
Karel Paar is a notable individual who shares the surname Paar and is recognized for his distinct personal achievements.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Karel Paar Target entity description: Karel Paar is a notable individual who shares the surname Paar and is recognized for his distinct personal achievements.
-
A.
Karel Hermánek
Karel Hermánek is a Czech actor known for his work in film, television, and theater, including a role in the 1993 war drama "Stalingrad."
-
B.
Josef Šebek
Josef Šebek is an actor known for appearing in the classic Czech New Wave film "A Blonde in Love."
-
C.
Karel Farský
Karel Farský was a Czech Catholic priest and theologian best known as the founder and first patriarch of the Czechoslovak Hussite Church in the early 20th century.
-
D.
Karel Šimka
Karel Šimka is a Czech lawyer and judge who serves as the president of the Supreme Administrative Court of the Czech Republic.
-
E.
Karel Klapálek
Karel Klapálek was a prominent Czechoslovak general and World War II resistance figure who played a key role in leading Czechoslovak forces on the Eastern Front.
- F. None of above. chosen
Provenance (5 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_69d8839174188190909f190097207065 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3abed67f88190afb1d392ff01a5e7 |
completed | April 18, 2026, 4:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d45013048190a8073f34820ca85a |
completed | May 10, 2026, 6:54 p.m. |
| NEDg | Description generation | batch_6a00d51835c48190b1a37de6ac25ceaa |
completed | May 10, 2026, 6:57 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00d59b96108190a0e55f01529a0b64 |
completed | May 10, 2026, 6:59 p.m. |
Created at: April 10, 2026, 5:21 a.m.