Triple
T17621954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Limanowa County |
E429728
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object | Mszana Dolna |
—
|
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: Mszana Dolna | Statement: [Limanowa County, containsTown, Mszana Dolna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mszana Dolna Context triple: [Limanowa County, containsTown, Mszana Dolna]
-
A.
Mszana Dolna
chosen
Mszana Dolna is a small town in southern Poland situated in a picturesque valley surrounded by the mountains of the Western Beskids.
-
B.
Tarnowskie Góry
Tarnowskie Góry is a historic town in southern Poland renowned for its UNESCO-listed silver, lead, and zinc mining heritage.
-
C.
Muszyna
Muszyna is a spa and tourist town in southern Poland, known for its mineral springs and scenic mountain surroundings near the Slovak border.
-
D.
Pszczyna
Pszczyna is a historic town in southern Poland known for its well-preserved castle complex and picturesque old town.
-
E.
Młociny
Młociny is a northern Warsaw neighborhood best known as the terminus of the city’s M1 metro line and a major transport hub.
- 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_69d889e37f308190a6aa0a69daff86c7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46db98c54819088dadec9f6bcc559 |
completed | April 19, 2026, 5:52 a.m. |
Created at: April 10, 2026, 5:52 a.m.