Datasets:

ISLAM-PO
/

documents-Egyptian-Arabic

This file explains the physical type of every column in every Parquet/CSV file and links it to the corresponding section in the main documentation README.md. Every row contains a direct README.md:line_number link for easy navigation.

How to Read the Table

Layer	Example	Verification Tool
Parquet Physical	`optional binary text (String)`	`pyarrow.parquet.ParquetFile(path).schema`
Arrow	`text: string`	`pf.schema_arrow`
Hugging Face Features	`Value(string)`	`pf.metadata.metadata[b'huggingface']`
Pandas dtype	`string` / `int64` / `float64`	`pd.read_parquet(path).dtypes`

optional = nullable (NULL allowed)
All strings are UTF-8
All numerics are little-endian

1. `egyptian_arabic` — `Egyptian-Arabic/*.parquet` (23,850,855 rows)

Linked to: README.md:173 (Data Instances §1) + README.md:397 (Appendix A.1) + README.md:70 (Dataset Structure)

Column	Physical Type	Arrow	HF	Pandas	Example
`text`	`optional binary (String)`	`string`	`Value(string)`	`string`	`عندى كام فكره...` / `November 2011`

Size: 10 shards, single column → streaming-friendly
Usage: README.md:110 Language Modeling
Verification code: README.md:420

2. `wikipedia` — `Egyptian_Arabic_Wikipedia_20230101/*.parquet` (728,337)

Linked to: README.md:188 + README.md:428 (Appendix A.2)

Important: First row contains literal value text → filter with df[df.text!="text"] (README.md:525)
No huggingface metadata → inferred automatically

3. `convs` — `egyptian_arabic_convs/*.parquet` (2,517 conversations)

Linked to: README.md:199 + README.md:438 (Appendix A.3)

| text | optional group (List) { repeated group list { struct { content: string, role: string } } } | list<element: struct<content:string, role:string>> | Sequence(Sequence(struct)) | object (list of dict) | [{"role":"user","content":"مين سقراط؟"}, {"role":"model","content":"سقراط كان..."}] |

HF Features:

"text": [{"content": {"dtype":"string"}, "role": {"dtype":"string"}}]

Parsing: json.loads(example["text"]) → README.md:211
Usage: Instruction-tuning / Chatbot README.md:110

4. `speech_whisper` — `egyptian-arabic-speech-dataset/*.parquet` (2,571)

Linked to: README.md:220 + README.md:457 (Appendix A.4) + README.md:465 (Whisper recipe)

Column	Parquet	Arrow	HF	Pandas	Shape
`input_features`	`optional group List { repeated group List { optional float } }`	`list<element: list<element: float>>`	`Sequence(Sequence(Value(float32)))`	`object`	`(80, 3000)` float32 → `np.stack()` = 0.96MB/row
`labels`	`optional group List { repeated group list { optional int64 } }`	`list<element: int64>`	`Sequence(Value(int64))`	`object`	`[50258,50272,50359,50363,...,50257]`

Tokens: 50258 <sot>, 50272 <ar>, 50359 <transcribe>, 50363 <notimestamps>, 50257 <eot> — same as openai/whisper
Storage: log-Mel 80 channels × 3000 frames (30s), padding ~ -0.598 for silence

5. `english_to_arabic` — `english-to-arabic/*.parquet` (33,299 unique)

Linked to: README.md:237 + README.md:474 (Appendix A.5) + README.md:369 (Splits)

Column	Parquet	Arrow	HF	Pandas	Example
`Egy`	`optional binary (String)`	`string`	`Value(string)`	`string`	`رضا فين؟`
`English`	`optional binary (String)`	`string`	`Value(string)`	`string`	`Where is Rida?`
`Egy_Text_Source`	`optional binary (String)`	`string`	`Value(string)`	`string`	`Al-Sabbagh 2023 Mendeley`

Sources share identical type: ArzEn 13,946 + EGY Songs 6,554 ×2 (duplicate) + NADI 12,799 → README.md:248
Dedup warning: Both Milion_Token* files are identical → README.md:525

6. `qa_trilingual` — `english-to-arabic/train.csv` (37,149)

Linked to: README.md:262 + README.md:486 (Appendix A.6) + dataset_info.yaml:3

Column	CSV Raw	Arrow (pandas)	HF Feature	Pandas	Example
`question`	`string` quoted	`large_string`	`Value(string)`	`string`	`مين اللي اخترع...؟`
`answer`	`string`	`large_string`	`Value(string)`	`string`	`تيم بيرنرز لي...`
`category`	`string`	`large_string`	`Value(string)`	`string`	`History` (48 values)
`sub_category`	`string`	`large_string`	`Value(string)`	`string`	`Discoveries`
`language`	`string` enum	`large_string`	`Value(string)`	`string`	`ar`/`ar_eg`/`en`
`question_char_length`	`int`	`int64`	`Value(int32)`	`int64`	`48`
`answer_char_length`	`int`	`int64`	`Value(int32)`	`int64`	`213`
`question_word_count`	`int`	`int64`	`Value(int32)`	`int64`	`8`
`answer_word_count`	`int`	`int64`	`Value(int32)`	`int64`	`37`

Distribution: ar_eg 12,451 | en 12,432 | ar 12,266 → README.md:277
Unique: The only CSV in the corpus

7-9. `balanced` / `unbalanced` / `uncategorized` — `balanced/*.parquet` etc.

Linked to: README.md:296 + README.md:504 (Appendix A.7) — identical 13-column schema

Column	Parquet	Arrow	HF	Pandas	Role
`page_title`	`optional binary (String)`	`string`	`Value(string)`	`string`	title
`creation_date`	`optional binary (String)`	`string`	`Value(string)`	`string`	`2020-05-08` stored as string, not date32 → `pd.to_datetime()`
`creator_name`	`optional binary (String)`	`string`	`Value(string)`	`string`	`HitomiAkane`
`total_edits`	`optional int64`	`int64`	`Value(int64)`	`int64`	count
`total_editors`	`optional int64`	`int64`	`Value(int64)`	`int64`	count
`top_editors`	`optional binary (String)`	`string`	`Value(string)`	`string`	`"['GhalyBot','HitomiAkane']"` as JSON string → needs `ast.literal_eval`
`bots_editors_percentage`	`optional double`	`double`	`Value(float64)`	`float64`	`50.0`
`humans_editors_percentage`	`optional double`	`double`	`Value(float64)`	`float64`	`50.0`
`total_bytes`	`optional int64`	`int64`	`Value(int64)`	`int64`	bytes
`total_chars`	`optional int64`	`int64`	`Value(int64)`	`int64`	chars
`total_words`	`optional int64`	`int64`	`Value(int64)`	`int64`	words
`page_text`	`optional binary (String)`	`string`	`Value(string)`	`string`	body (461–1002 avg)
`label`	`optional binary (String)`	`string`	`Value(string)`	`string`	`Human-generated` / `Template-translated`

Sizes: balanced 20K (50% / 50%) — unbalanced 166K (93% Template) — uncategorized 569K → README.md:315
Warning: top_editors looks like list but is string → README.md:526

10. `reviews_spam` — `part 1 data/*.parquet` (60,000 — 26 columns)

Linked to: README.md:327 + README.md:528 (Appendix A.8) + README.md:477 (Training Recipe D)

#	Column	Parquet	Arrow	HF	Pandas	Example / Range
1	`user_id`	`int64`	`int64`	`Value(int64)`	`int64`	`48592`
2	`product_id`	`int64`	`int64`	`Value(int64)`	`int64`	`3791`
3	`original_review`	`binary (String)`	`string`	`Value(string)`	`string`	`Love this place!` (English)
4	`translated_review`	`binary (String)`	`string`	`Value(string)`	`string`	`بحب المكان ده!` (dialectal)
5	`normalized_translated_review`	`binary (String)`	`string`	`Value(string)`	`string`	`بحب المكان ده! في وقت من الاوقات` (normalized)
6	`date`	`binary (String)`	`string`	`Value(string)`	`string`	`2014-03-21`
7	`rating`	`int64`	`int64`	`Value(int64)`	`int64`	`1-5`
8	`sentiment_label`	`binary (String)`	`string`	`Value(string)`	`string`	`positive/negative/neutral`
9	`positive_normalized_score`	`double`	`double`	`Value(float64)`	`float64`	`0.0-1.0`
10	`neutral_normalized_score`	`double`	`double`	`Value(float64)`	`float64`	`0.0-1.0`
11	`negative_normalized_score`	`double`	`double`	`Value(float64)`	`float64`	`0.0-1.0`
12	`spam_hit_score`	`int64`	`int64`	`Value(int64)`	`int64`	`0` (46K) / `1` (2.8K)
13	`arabic_num_words`	`int64`	`int64`	`Value(int64)`	`int64`	`112`
14	`entropy1`	`double`	`double`	`Value(float64)`	`float64`	`3.5-8.0`
15	`entropy2`	`double`	`double`	`Value(float64)`	`float64`	`3.5-8.0`
16	`first_review_date`	`binary (String)`	`string`	`Value(string)`	`string`	`2012-01-10`
17	`last_review_date`	`binary (String)`	`string`	`Value(string)`	`string`	`2014-05-01`
18	`review_gap_days`	`int64`	`int64`	`Value(int64)`	`int64`	`0-2000`
19	`review_count`	`int64`	`int64`	`Value(int64)`	`int64`	`1-500`
20	`product_avg_rating`	`double`	`double`	`Value(float64)`	`float64`	`2.5-5.0`
21	`rating_deviation`	`double`	`double`	`Value(float64)`	`float64`	`-3 .. +3`
22	`product_first_review_date`	`binary (String)`	`string`	`Value(string)`	`string`	`2011-06-15`
23	`days_since_first_review`	`int64`	`int64`	`Value(int64)`	`int64`	`0-4000`
24	`user_tenure_days`	`int64`	`int64`	`Value(int64)`	`int64`	`0-4000`
25	`label`	`int64`	`int64`	`Value(int64)`	`int64`	`0/1`
26	`label_str`	`binary (String)`	`string`	`Value(string)`	`string`	`authentic/fake` (50/50)

Note: label (int) and label_str (string) are dual encodings of the same binary target → use label_str for readability and label for loss

Quick Link Matrix (File → Config → README Section)

File Pattern	Config `load_dataset`	README Section
`Egyptian-Arabic/*.parquet`	`egyptian_arabic`	`README.md:173` + `README.md:397`
`Egyptian_Arabic_Wikipedia_20230101/*.parquet`	`wikipedia`	`README.md:188` + `README.md:428`
`egyptian_arabic_convs/*.parquet`	`convs`	`README.md:199` + `README.md:438`
`egyptian-arabic-speech-dataset/*.parquet`	`speech_whisper`	`README.md:220` + `README.md:457`
`english-to-arabic/*.parquet`	`english_to_arabic`	`README.md:237` + `README.md:474`
`english-to-arabic/train.csv`	`qa_trilingual`	`README.md:262` + `README.md:486`
`balanced/*.parquet`	`balanced`	`README.md:296` + `README.md:504`
`unbalanced/*.parquet`	`unbalanced`	`README.md:296` + `README.md:504`
`uncategorized/*.parquet`	`uncategorized`	`README.md:296` + `README.md:504`
`part 1 data/*.parquet`	`reviews_spam`	`README.md:327` + `README.md:528`

Storage & Cross-Link Notes

All Parquet files are Snappy-compressed with dictionary-encoded strings — README.md:578
Files without b'huggingface' metadata (e.g., wikipedia) are inferred automatically at load_dataset time
To validate a new shard before contributing:

import pyarrow.parquet as pq
pf = pq.ParquetFile("path.parquet")
assert pf.schema_arrow.equals(expected)  # compare with README.md:528

Widest: reviews_spam (26 columns) → slowest to scan, Tallest: egyptian_arabic (23M) → use streaming=True → README.md:594

Summary: This file is the physical map, and README.md is the logical map. Keep them together when uploading to Hugging Face.

Data Types in Files — Linked to README.md

How to Read the Table

1. egyptian_arabic — Egyptian-Arabic/*.parquet (23,850,855 rows)

2. wikipedia — Egyptian_Arabic_Wikipedia_20230101/*.parquet (728,337)

3. convs — egyptian_arabic_convs/*.parquet (2,517 conversations)

4. speech_whisper — egyptian-arabic-speech-dataset/*.parquet (2,571)

5. english_to_arabic — english-to-arabic/*.parquet (33,299 unique)

6. qa_trilingual — english-to-arabic/train.csv (37,149)

7-9. balanced / unbalanced / uncategorized — balanced/*.parquet etc.

10. reviews_spam — part 1 data/*.parquet (60,000 — 26 columns)