Triple
T10461385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Śnieżka |
E246681
|
entity |
| Predicate | hasGermanName |
P1435
|
FINISHED |
| Object | Schneekoppe |
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: Schneekoppe | Statement: [Śnieżka, hasGermanName, Schneekoppe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schneekoppe Context triple: [Śnieżka, hasGermanName, Schneekoppe]
-
A.
Snoge
Snoge is the historic 17th-century Portuguese-Israelite synagogue in Amsterdam, renowned as one of the oldest and best-preserved Sephardic synagogues in Europe.
-
B.
Snowlets
Snowlets are the four snowy owl mascots created to represent the 1998 Winter Olympics in Nagano, Japan.
-
C.
Śnieżnica
Śnieżnica is a mountain peak in southern Poland, located in the Beskid Wyspowy range and popular for hiking and winter sports.
-
D.
Snowman
Snowman is the post-apocalyptic survivor and narrator of Margaret Atwood’s dystopian novel "Oryx and Crake," through whose perspective the story’s ruined world and its origins are revealed.
-
E.
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.
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d50883b62c819082711b8c9fd968e3 |
completed | April 7, 2026, 1:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d89fcc84b48190a39de0d9b9111ebd |
completed | April 10, 2026, 6:59 a.m. |
Created at: April 6, 2026, 12:19 p.m.