Triple
T6613137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silesian Voivodeship |
E149284
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Jaworzno |
E251901
|
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: Jaworzno | Statement: [Silesian Voivodeship, containsCity, Jaworzno]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jaworzno Context triple: [Silesian Voivodeship, containsCity, Jaworzno]
-
A.
Jaworzno
chosen
Jaworzno is a city in southern Poland, located in the Silesian Voivodeship and known for its industrial heritage and role in the Upper Silesian urban area.
-
B.
Kociewie
Kociewie is an ethnocultural region in northern Poland known for its distinct folk traditions, dialect, and rural landscapes.
-
C.
Jedwabno
Jedwabno is a small town in northern Poland located within the Warmian-Masurian Voivodeship, an area known for its lakes and forests.
-
D.
Zduńska Wola
Zduńska Wola is a town in central Poland known historically as a textile and industrial center.
-
E.
Tczew
Tczew is a historic town in northern Poland on the Vistula River, known for its important railway bridges and role as a regional transport hub.
- 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_69c687ebc680819094caf71faba2efe2 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6af3890408190a0edf2f813b93196 |
completed | March 27, 2026, 4:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2693f054081909fe58a252bd76226 |
completed | April 5, 2026, 1:53 p.m. |
Created at: March 27, 2026, 1:57 p.m.