Triple
T21436031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Svika Pick |
E528810
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Wrocław, 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: Wrocław, Poland | Statement: [Svika Pick, placeOfBirth, Wrocław, Poland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wrocław, Poland Context triple: [Svika Pick, placeOfBirth, Wrocław, Poland]
-
A.
Wrocanka, Poland
Wrocanka, Poland is a small village in southeastern Poland known as the birthplace of former Polish communist leader Stanisław Kania.
-
B.
Wrocław
chosen
Wrocław is a major historic city in southwestern Poland, known for its picturesque Old Town, numerous bridges over the Oder River, and role as a cultural and academic center.
-
C.
Katowice
Katowice is a major industrial and cultural city in southern Poland, known as the capital of the Silesian region.
-
D.
Gorzów Wielkopolski, Poland
Gorzów Wielkopolski is a city in western Poland, known as one of the two capitals of the Lubusz Voivodeship and an important regional industrial and cultural center.
-
E.
Tychy, Poland
Tychy, Poland is an industrial city in the Silesian region known for its major automotive manufacturing plants and brewing industry.
- 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_69e0c4569fa081908101baa24f8745db |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e8b5373994819088fbd82f31c3b0c8 |
completed | April 22, 2026, 11:47 a.m. |
Created at: April 16, 2026, 6:02 p.m.