Triple
T4971336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Klemens |
E111656
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Klement |
E111656
|
NE FINISHED |
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: Klement | Statement: [Klemens, hasVariant, Klement]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Klement Context triple: [Klemens, hasVariant, Klement]
-
A.
Klemens
chosen
Klemens is a given name, primarily used in German-speaking and Central European countries, that corresponds to the Latin-derived name Clemens.
-
B.
Timotej
Timotej is a masculine given name, common in Slavic countries, that is equivalent to Timothy.
-
C.
Jozef
Jozef is a masculine given name of Hebrew origin, commonly used in Central and Eastern Europe as a variant of Joseph.
-
D.
Julijan
Julijan is a given name, commonly used in Slavic regions, that corresponds to the name Julian.
-
E.
Ferdl
Ferdl is a German diminutive form of the male given name Ferdinand, commonly used as an affectionate nickname.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69bd441a0eb481908050fa4273b19eae |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd7213bf0081909b3c496f1804dc4c |
completed | March 20, 2026, 4:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be81fa9108819089a6258e3a88f0cb |
completed | March 21, 2026, 11:33 a.m. |
Created at: March 20, 2026, 1:33 p.m.