Triple
T21662285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jiří Bělohlávek |
E534622
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Jiří |
—
|
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: Jiří | Statement: [Jiří Bělohlávek, givenName, Jiří]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jiří Context triple: [Jiří Bělohlávek, givenName, Jiří]
-
A.
Jiří
chosen
Jiří is a common Czech male given name, equivalent to George in English.
-
B.
Zdeněk
Zdeněk is a Czech given name commonly used for males, equivalent to the English name Sidney or Dennis in some contexts.
-
C.
Jiri
Jiri is a small town in eastern Nepal that serves as a traditional starting point for overland treks into the Everest region.
-
D.
Zbyněk
Zbyněk is a masculine given name of Czech origin commonly used in the Czech Republic and among Czech-speaking communities.
-
E.
Jaroslav
Jaroslav is a masculine given name of Slavic origin, commonly used in Czech, Slovak, Polish, and other Slavic languages.
- 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_69e0c467e1f48190af2650b19175abc4 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef6c0883d481908dfdc66832c34d74 |
completed | April 27, 2026, 2 p.m. |
Created at: April 16, 2026, 6:36 p.m.