Triple
T5870118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nowak |
E130494
|
entity |
| Predicate | rankByFrequencyInPoland |
P67630
|
FINISHED |
| Object | one of the most common surnames in Poland |
—
|
LITERAL 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: one of the most common surnames in Poland | Statement: [Nowak, rankByFrequencyInPoland, one of the most common surnames in Poland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankByFrequencyInPoland Context triple: [Nowak, rankByFrequencyInPoland, one of the most common surnames in Poland]
-
A.
hasNameInPolish
Indicates that an entity is associated with a specific name or label expressed in the Polish language.
-
B.
officialNamePolish
Indicates the official or legally recognized name of an entity as expressed in the Polish language.
-
C.
rankedByNumberOfNativeSpeakers
Indicates that entities are ordered or classified according to how many native speakers they have.
-
D.
populationRankInLithuania
Indicates the relative position of an entity in terms of population size compared to other entities within Lithuania.
-
E.
hasFrequencyRankInEngland
Indicates that an entity (such as a name or term) has a specific position in a ranked list based on how frequently it occurs in England.
- F. None of above. chosen
Provenance (4 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_69c0085047dc8190af24e311edad3c07 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ffaef081909faaa7f420a3b9b7 |
completed | March 22, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69c03347e51c81909053bcf34e3b88ab |
completed | March 22, 2026, 6:22 p.m. |
| PDg | Predicate description generation | batch_69c044fe17d08190b9bf47b13863ef52 |
completed | March 22, 2026, 7:37 p.m. |
Created at: March 22, 2026, 3:56 p.m.