Triple
T20619755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pavel Pekar |
E506667
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Pavel |
—
|
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: Pavel | Statement: [Pavel Pekar, hasGivenName, Pavel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pavel Context triple: [Pavel Pekar, hasGivenName, Pavel]
-
A.
Pavel
chosen
Pavel is a Slavic given name, equivalent to the English name Paul.
-
B.
Vadim
Vadim is a masculine given name of Slavic origin, commonly used in Russia and other Eastern European countries.
-
C.
Pavlo
Pavlo is a masculine given name of Slavic origin, commonly used in Ukrainian and other Eastern European cultures as a form of "Paul."
-
D.
Petr
Petr is a common Slavic given name, equivalent to Peter in English.
-
E.
Pavel Kadochnikov
Pavel Kadochnikov was a prominent Soviet film and theater actor known for his leading roles in classic Russian cinema of the mid-20th century.
- 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_69e0b4bc90988190ac360aaf645efc1d |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6abe0e22c81909f6efe21518e33f0 |
completed | April 20, 2026, 10:42 p.m. |
Created at: April 16, 2026, 11:41 a.m.