Triple
T12845247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jelenia Góra |
E307156
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object | Sobieszów |
E896101
|
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: Sobieszów | Statement: [Jelenia Góra, hasDistrict, Sobieszów]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sobieszów Context triple: [Jelenia Góra, hasDistrict, Sobieszów]
-
A.
Sobieszów
chosen
Sobieszów is a district of the city of Jelenia Góra in southwestern Poland, known for its proximity to the Karkonosze Mountains and the historic Chojnik Castle.
-
B.
Sulechów
Sulechów is a small town in western Poland, known as the birthplace of Nobel Prize–winning writer Olga Tokarczuk.
-
C.
Świętoszów
Świętoszów is a village in southwestern Poland known for its large military training grounds and long-standing role as a garrison town.
-
D.
Dobczyce
Dobczyce is a small historic town in southern Poland, known for its medieval castle and picturesque setting by the Raba River and Dobczyce Lake.
-
E.
Rakowice
Rakowice is a historic district in Kraków, Poland, known for its large military cemetery and proximity to the city center.
- 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_69d7bdf5e7cc8190be357278bc5ba3bb |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96ff3a7208190b93f6292ed5efc07 |
completed | April 10, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0035428e608190b8bb41dabda044d1 |
completed | May 10, 2026, 7:35 a.m. |
Created at: April 9, 2026, 5:36 p.m.