Triple
T24157428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Łukasz Nowak |
E598722
|
entity |
| Predicate | surnameFrequencyContext |
P29278
|
FINISHED |
| Object | Nowak is one of the most common surnames in Poland |
—
|
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: Nowak is one of the most common surnames in Poland | Statement: [Łukasz Nowak, surnameFrequencyContext, Nowak is one of the most common surnames in Poland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: surnameFrequencyContext Context triple: [Łukasz Nowak, surnameFrequencyContext, Nowak is one of the most common surnames in Poland]
-
A.
hasGivenNameFrequency
Indicates the frequency or commonness with which a particular given name occurs within a specified population or context.
-
B.
hasSurnameFrequency
Indicates that a surname occurs with a specified frequency or rate within a given population or dataset.
-
C.
namePopularityRegion
Indicates the geographic region or area in which a particular name has a certain level of popularity or usage.
-
D.
isAmongMostCommonSurnamesIn
chosen
Indicates that a surname ranks within the group of most frequently occurring surnames in a specified region or population.
-
E.
hasNameGenderUsage
Indicates that a particular name is used with a specific gender or set of genders in a given context.
- F. None of above.
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_69e288cb0a3081909ef221744f274384 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1e0e5bdb48190aa2d369942b85220 |
completed | April 29, 2026, 10:43 a.m. |
| PD | Predicate disambiguation | batch_69f176585f3481909beb907de252cd98 |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 11:31 p.m.