The dataset viewer is not available for this split.
Error code: FeaturesError
Exception: ParserError
Message: Error tokenizing data. C error: Expected 1 fields in line 8, saw 2
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 3496, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2257, in _head
return next(iter(self.iter(batch_size=n)))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2461, in iter
for key, example in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1952, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1974, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 503, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 350, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/csv/csv.py", line 190, in _generate_tables
for batch_idx, df in enumerate(csv_file_reader):
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/parsers/readers.py", line 1843, in __next__
return self.get_chunk()
^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/parsers/readers.py", line 1985, in get_chunk
return self.read(nrows=size)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/parsers/readers.py", line 1923, in read
) = self._engine.read( # type: ignore[attr-defined]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 234, in read
chunks = self._reader.read_low_memory(nrows)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "pandas/_libs/parsers.pyx", line 850, in pandas._libs.parsers.TextReader.read_low_memory
File "pandas/_libs/parsers.pyx", line 905, in pandas._libs.parsers.TextReader._read_rows
File "pandas/_libs/parsers.pyx", line 874, in pandas._libs.parsers.TextReader._tokenize_rows
File "pandas/_libs/parsers.pyx", line 891, in pandas._libs.parsers.TextReader._check_tokenize_status
File "pandas/_libs/parsers.pyx", line 2061, in pandas._libs.parsers.raise_parser_error
pandas.errors.ParserError: Error tokenizing data. C error: Expected 1 fields in line 8, saw 2Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
π Hamed Behrouzi β Identity Graph Dataset (Q1 Edition, v02)
This dataset represents the Q1 edition of my multilingual Identity Graph Project, designed for:
- AI research
- semantic modeling
- cross-platform identity alignment
- structured knowledge engineering
- graph-based reasoning
It provides a high-level model of my professional, academic, and creative digital identity across verified platforms.
π Dataset Contents
The dataset includes:
1. nodes.csv
A structured list of all canonical entities contained in the identity graph, including:
- Person identifiers
- Creative works
- Academic profiles
- Film/VFX credits
- Research objects (DOIs, Zenodo entries)
- External platform links
| column | description |
|---|---|
| id | unique node identifier |
| label | human-readable entity name |
| type | entity type (person, article, dataset, platform, etc.) |
2. edges.csv
Typed graph relationships between entities.
| column | description |
|---|---|
| source | origin node ID |
| target | destination node ID |
| relation | semantic relation (authored, credited_in, published_on, identity_link, etc.) |
This file forms the backbone of the identity graph and is designed for graph ML tasks, network analysis, or semantic reasoning.
3. identityGraph.jsonld
A formal JSON-LD representation of the entire identity graph schema.
It is suitable for:
- semantic web tools
- linked-data systems
- AI reasoning engines
- schema validation
4. metadata.json
General metadata describing:
- dataset structure
- fields
- versioning
- semantic notes
5. README.md
You are reading it.
π Purpose of This Dataset
This dataset is intended to support research in:
- identity resolution
- knowledge graph alignment
- multimodal personal identity modeling
- semantic graph design
- AI-driven profile integration
- ethical AI metadata systems
It mirrors a real-world, multi-platform digital identity structure using verified sources:
- ORCID
- Zenodo
- IMDb / TMDb / Metacritic
- GitHub
- Personal website
- Wikidata & related systems
π Version
Q1 Edition, v02 β December 2025
This version improves:
- node/edge normalization
- JSON-LD schema clarity
- multi-platform alignment
- dataset portability
π Citation
π BibTeX Citation
@dataset{behrouzi_identity_graph_q1_v02_2025,
author = {Hamed Behrouzi},
title = {Identity Graph Dataset (Q1 Edition, v02)},
year = {2025},
month = dec,
publisher = {HuggingFace Datasets},
url = {https://huggingface.co/datasets/HamedBehrouzi/HamedBehrouzi-IdentityGraph-Q1-v02},
note = {Multilingual professional identity graph dataset including nodes.csv, edges.csv, schema.jsonld, and metadata.json.}
}
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