---
pretty_name: WALS-bench
license: cc-by-4.0
multilinguality: multilingual

configs:
- config_name: WALS-features-format1
  data_files:
  - split: train
    path: "WALS-benchmark-feat.jsonl"

- config_name: WALS-features-with-languages-format2
  data_files:
  - split: train
    path: "WALS-benchmark-feat-with-lang.jsonl"
---

---

WALS-bench: A Metalinguistic Benchmark Based on WALS

### Overview 
This is a large-scale multilingual benchmark that evaluates metalinguistic knowledge in large language models using typological features from the World Atlas of Language Structures (WALS). The benchmark covers 192 linguistic features across 2,660 languages.

### Benchmark Format
The benchmark is available in two formats:

Format 1: 192-question version - one question per feature, under which all languages with a corresponding ground truth value for that feature are listed.

Format 2: 76,475-question version - one question per feature-language pair with a corresponding ground truth value, fully expanded across all languages.

### Task Definition
Given a linguistic question derived from a WALS feature with a set of possible answers for a specific language, the model must predict the correct typological category for that language. 

### Prompt
The benchmark is evaluated using a single prompt. The prompt template used in our experiment:
{question} The options are {possible_answers}. Answer by choosing one option. Do not provide an explanation.

### Proposed Data Splits 
Validation set:
29 features - 5A, 12A, 17A, 21B, 28A, 33A, 35A, 45A, 49A, 56A, 58B, 73A, 80A, 81A, 86A, 89A, 90A, 90D, 92A, 98A, 109B, 111A, 118A, 124A, 131A, 137A, 143A, 144M, 144X
Test set: 
29 features - 6A, 10A, 15A, 25A, 26A, 36A, 42A, 46A, 55A, 67A, 71A, 77A, 85A, 87A, 90C, 94A, 97A, 106A, 107A, 112A, 117A, 125A, 127A, 130B, 136A, 139A, 143C, 144Q, 144W
Training set:
134 features - the remaining features

### Data Format
FORMAT 1:
Each feature is stored in JSONL format: 
{"feature_id": "1A", 
"feature_name": "Consonant Inventories", 
"domain": "Phonology", 
"question": "How large is the consonant inventory in the `<LANGUAGE>` language?", 
"possible_answers": "Small; Moderately small; Average; Moderately large; Large", 
"ground_truth": {"Abipón": "Moderately small", "Abkhaz": "Large", "Alabama": "Small", "Aché": "Small" /* additional languages omitted/}}

`<LANGUAGE>` is replaced with a specific language name at inference time. 

FORMAT 2:
Each feature is stored in JSONL format: 
{"feature_id": "1A", 
"feature_name": "Consonant Inventories", 
"domain": "Phonology", 
"question": "How large is the consonant inventory in the Abipón language?", 
"possible_answers": "Small; Moderately small; Average; Moderately large; Large", 
"language_name": "Abipón",
"ISO639-3": "axb", 
"ground_truth": "Moderately small"}

### Linguistic Feature Coverage
Word Order: 56 features
Nominal Categories: 29 features
Simple Clauses: 26 features
Phonology: 20 features
Verbal Categories: 17 features
Lexicon: 13 features
Morphology: 12 features
Nominal Syntax: 8 features
Complex Sentences: 7 features
Sign Languages: 2 features
Clicks (Other): 1 feature
Writing System (Other): 1 feature

### Language Coverage
Total number of languages covered: 2,660 world languages. 

### Evaluation
Predictions are evaluated by comparing model outputs to the WALS ground-truth categories. 

### Licence
The original WALS data is licensed under CC BY 4.0. The data has been adapted for use in this benchmark. 

Source:
Dryer, Matthew S. & Haspelmath, Martin (eds.).  
World Atlas of Language Structures Online.  
Max Planck Institute for Evolutionary Anthropology.  
https://wals.info