Triple
T22614208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jan Novák |
E566796
|
entity |
| Predicate | studentOf |
P48
|
FINISHED |
| Object | Alois Hába |
—
|
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: Alois Hába | Statement: [Jan Novák, studentOf, Alois Hába]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alois Hába Context triple: [Jan Novák, studentOf, Alois Hába]
-
A.
Alois Hába
chosen
Alois Hába was a Czech composer and music theorist renowned for his pioneering work in microtonal music and quarter-tone composition.
-
B.
Franz Roubal
Franz Roubal was a mountaineer known for making the first recorded ascent of the Polish peak Wielki Giewont.
-
C.
Rudolf Firkusny
Rudolf Firkusny was a renowned Czech-born pianist celebrated for his interpretations of Czech composers, especially Janáček and Dvořák, and for his distinguished international concert and recording career.
-
D.
Emil Berna
Emil Berna was a Swiss cinematographer known for his influential work on mid-20th-century European films.
-
E.
Josef Beránek
Josef Beránek is a Czech former professional ice hockey player known for his career in the NHL and various European leagues.
- 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_69e245884860819081046ce07d5872c4 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f167ecc7188190bf41fe2177d48e6c |
completed | April 29, 2026, 2:07 a.m. |
Created at: April 17, 2026, 2:58 p.m.