Triple
T11854061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Noteć |
E281986
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Noteć Górna |
E948959
|
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: Noteć Górna | Statement: [Noteć, hasPart, Noteć Górna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Noteć Górna Context triple: [Noteć, hasPart, Noteć Górna]
-
A.
Noteć Dolna
chosen
Noteć Dolna is the lower course and surrounding valley region of the Noteć River in north-central Poland, known for its wetlands and agricultural landscapes.
-
B.
Muszyna
Muszyna is a spa and tourist town in southern Poland, known for its mineral springs and scenic mountain surroundings near the Slovak border.
-
C.
Gurwik-Górska
Gurwik-Górska is the Polish maiden surname of the renowned Art Deco painter Tamara de Lempicka.
-
D.
Świątniki Górne
Świątniki Górne is a small town in southern Poland, situated near Kraków and known for its traditional locksmithing and metalworking industries.
-
E.
Sucha Beskidzka
Sucha Beskidzka is a small historic town in southern Poland, known for its picturesque Beskid mountain setting and its Renaissance-style castle.
- 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_69d6ab287ba48190a5178779fd19b9b7 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a697f4108190af984932d2118472 |
completed | April 10, 2026, 7:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f41798b5888190b615d4e23fe3d55e |
completed | May 1, 2026, 3:01 a.m. |
Created at: April 8, 2026, 9:43 p.m.