Datasets:
metadata
license: mit
task_categories:
- text-generation
tags:
- knowledge-graph
- tool-calling
- trajectories
size_categories:
- 1M<n<10M
configs:
- config_name: triplets
data_files: triplets_all.jsonl
default: true
- config_name: trajectories_query_relations
data_files: trajectories_query_relations_1m.jsonl
- config_name: trajectories_get_neighbors
data_files: trajectories_get_neighbors_1m.jsonl
- config_name: paths
data_files: paths_1m.jsonl
WikiKG Trajectories
2M tool-calling trajectories + 366k triplets from Wikipedia knowledge graph.
Configurations
| Config | Records | Size | Description |
|---|---|---|---|
triplets (default) |
365,923 | 30 MB | Subject-relation-object triplets |
trajectories_query_relations |
1,000,000 | 5.1 GB | Tool-call conversations (query_relations style) |
trajectories_get_neighbors |
1,000,000 | 5.0 GB | Tool-call conversations (get_neighbors style) |
paths |
1,500,000 | 230 MB | Random walk paths through the graph |
Tool-Calling Styles
Each trajectory is a multi-turn conversation where an LLM calls tools to traverse the knowledge graph:
- query_relations: Calls
query_relations(subject, obj, rel_type)to filter triplets by entity/relation - get_neighbors: Calls
get_neighbors(entity, direction)for graph exploration
Example Trajectory
{
"messages": [
{"role": "user", "content": "Starting from Einstein, follow FIELD_OF forward, then STUDIED_BY backward. What's the final entity?"},
{"role": "assistant", "tool_calls": [{"function": {"name": "query_relations", "arguments": "{\"subject\": \"Einstein\", \"rel_type\": \"FIELD_OF\"}"}}]},
{"role": "tool", "content": "[{\"subject\": \"Einstein\", \"relation\": \"FIELD_OF\", \"object\": \"Physics\"}]"},
...
],
"metadata": {
"path_entities": ["Einstein", "Physics", "Feynman"],
"path_relations": ["FIELD_OF", "STUDIED_BY"],
"num_hops": 2
}
}
Example Triplet
{"subject": "GirardDesargues", "relation": "CREATOR_OF", "object": "DesarguesianPlane"}
Source
Generated from wiki-kg-dataset containing 45,416 Wikipedia articles and 180+ relation types.
Usage
from datasets import load_dataset
# Load default (triplets)
ds = load_dataset("AutomatedScientist/wikikg-trajectories")
# Load specific config
ds = load_dataset("AutomatedScientist/wikikg-trajectories", "trajectories_query_relations")
ds = load_dataset("AutomatedScientist/wikikg-trajectories", "trajectories_get_neighbors")
ds = load_dataset("AutomatedScientist/wikikg-trajectories", "paths")