SDVM/xtreme-PAN-X.de

SDVM Refined PAN-X.de (XTREME NER)

This is an enhanced version of the PAN-X German NER dataset from the XTREME benchmark (config: PAN-X.de), refined by SDVM (Synthetic Data Vending Machine) to improve token quality for Named Entity Recognition.

Refinement

The original PAN-X.de dataset is derived from WikiANN/Wikipedia and contains various artifacts from the extraction process. SDVM applied automated token refinement that removes Wikipedia markup noise while preserving entity annotations:

• Markup token removal: Removed ~8.5% of tokens that were Wikipedia formatting artifacts (bold markers, quote marks, section headers, template brackets, etc.)
• Redirect cleanup: Removed WEITERLEITUNG (German Wikipedia redirect markers)
• Embedded markup stripping: Cleaned tokens containing partial markup (e.g., Friedrichsaue with trailing brackets)
• Tag continuity repair: Automatically fixed B-/I- tag sequences after token removal to maintain valid IOB2 format

Dataset Structure

Each example contains both the original and refined versions:

Column	Description
tokens	Original token sequence
ner_tags	Original NER tags (IOB2 format)
tokens_refined	Cleaned token sequence
ner_tags_refined	Adjusted NER tags for refined tokens
langs	Language tags

NER Labels

ID	Tag
0	O
1	B-PER
2	I-PER
3	B-ORG
4	I-ORG
5	B-LOC
6	I-LOC

Example

Original: ['**', "''", 'Lou', 'Salome', "''", '.'] with tags [O, O, B-PER, I-PER, O, O]

Refined: ['Lou', 'Salome', '.'] with tags [B-PER, I-PER, O]

Usage

from datasets import load_dataset

# Load the refined dataset
ds = load_dataset("SDVM/xtreme-PAN-X.de")

# Use refined columns for training
train_tokens = ds["train"]["tokens_refined"]
train_tags = ds["train"]["ner_tags_refined"]

# Or use original columns for comparison
orig_tokens = ds["train"]["tokens"]
orig_tags = ds["train"]["ner_tags"]

Source

• Original dataset: google/xtreme (PAN-X.de config)
• Reference: Chapter 4 of Natural Language Processing with Transformers
• Refinement by: SDVM