Triple
T7146677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karkonosze |
E166586
|
entity |
| Predicate | highestPoint |
P210
|
FINISHED |
| Object | Śnieżka |
E246681
|
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: Śnieżka | Statement: [Karkonosze, highestPoint, Śnieżka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Śnieżka Context triple: [Karkonosze, highestPoint, Śnieżka]
-
A.
Śnieżka
chosen
Śnieżka is a prominent mountain peak on the border of Poland and the Czech Republic, renowned as the tallest summit in the Sudetes range and a popular hiking destination.
-
B.
Śnieżnica
Śnieżnica is a mountain peak in southern Poland, located in the Beskid Wyspowy range and popular for hiking and winter sports.
-
C.
Blizne
Blizne is a village in southeastern Poland best known for its historic wooden All Saints Church, a UNESCO World Heritage Site.
-
D.
Děčínský Sněžník
Děčínský Sněžník is a prominent table mountain in the Czech Republic known for its sandstone cliffs and panoramic views over the surrounding Elbe Sandstone landscape.
-
E.
Frunze
Frunze is a surname most notably associated with Mikhail Frunze, a prominent Bolshevik leader and Red Army commander during the Russian Civil War.
- 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_69c68886779c8190a8e3fbabffe68253 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e7d4f3388190941f03fd80b0c223 |
completed | March 27, 2026, 8:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7ada12a848190b6e98e0b1a258c17 |
completed | March 28, 2026, 10:29 a.m. |
Created at: March 27, 2026, 2:46 p.m.