Triple
T6577273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franciszek Kleeberg |
E157199
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Franciszek |
E289085
|
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: Franciszek | Statement: [Franciszek Kleeberg, givenName, Franciszek]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Franciszek Context triple: [Franciszek Kleeberg, givenName, Franciszek]
-
A.
Franciszek
chosen
Franciszek is a masculine given name of Latin origin, commonly used in Poland and other Slavic countries.
-
B.
Józef
Józef is a masculine given name of Hebrew origin, widely used in Poland and other Slavic countries as a form of Joseph.
-
C.
Paweł
Paweł is a common Polish given name, equivalent to the English name Paul.
-
D.
Michał
Michał is a Polish given name commonly used for males, equivalent to the English name Michael.
-
E.
Wincenty
Wincenty is a masculine given name of Slavic origin, particularly common in Poland.
- 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_69c6882b3a108190b3a9eb343ae4162c |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ae74fd90819091d67eec6381d5e0 |
completed | March 27, 2026, 4:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6cba5cc708190a8748160a7878b8f |
completed | March 27, 2026, 6:25 p.m. |
Created at: March 27, 2026, 1:54 p.m.