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---
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license: apache-2.0
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task_categories:
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- question-answering
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language:
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- th
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- en
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tags:
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- art
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pretty_name: Lexitron 2.0 Prompt Finetuning Dataset
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size_categories:
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- 100K<n<1M
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maintainer: Kobkrit Viriyayudhakorn (kobkrit@iapp.co.th)
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---
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# Lexitron 2.0 Prompt Finetuning Dataset
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This dataset is derived from Lexitron 2.0, a Thai-English dictionary developed by NECTEC. It has been processed and formatted for prompt finetuning tasks. The original dataset is from: https://opend-portal.nectec.or.th/dataset/lexitron-2-0
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##
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<|
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ควา
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---
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license: apache-2.0
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task_categories:
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- question-answering
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language:
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- th
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- en
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tags:
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- art
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pretty_name: Lexitron 2.0 Prompt Finetuning Dataset
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size_categories:
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- 100K<n<1M
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maintainer: Kobkrit Viriyayudhakorn (kobkrit@iapp.co.th)
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---
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# Lexitron 2.0 Prompt Finetuning Dataset
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This dataset is derived from Lexitron 2.0, a Thai-English dictionary developed by NECTEC. It has been processed and formatted for prompt finetuning tasks. The original dataset is from: https://opend-portal.nectec.or.th/dataset/lexitron-2-0
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## Maintainer
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Kobkrit Viriyayudhakorn (kobkrit@iapp.co.th)
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## Dataset Description
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The dataset consists of two main files:
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1. `lexitron2_telex_finetune.qwen2.txt` - Thai to English lexicon entries in Qwen2 conversation format
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2. `lexitron2_telex_finetune.jsonl` - Thai to English lexicon entries in JSONL format
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Each file contains dictionary entries formatted in their respective formats.
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## Syntax and Example Dataset
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### Syntax
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The dataset files follow specific formats for ease of use in prompt finetuning tasks.
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#### `lexitron2_telex_finetune.jsonl`
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Each entry in this file follows the generic prompt format:
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```json
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{
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"instruction": "<instruction in English or Thai>",
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"output": "<translation or definition in Thai>"
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}
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```
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- **instruction**: A string that provides the translation task or query. It can be in English or Thai.
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- **output**: A string that provides the translation or definition in Thai.
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#### `lexitron2_telex_finetune.qwen2.txt`
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Each entry in this file follows the Qwen2 conversation format:
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```text
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<|im_start|>system\n
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คุณคือผู้ช่วยตอบคำถามที่ฉลาดและซื่อสัตย์<|im_end|>\n
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<|im_start|>user\n
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คำว่า 'example_word' แปลว่าอะไร<|im_end|>\n
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<|im_start|>assistant\n
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คำว่า 'example_word' เป็นคำประเภท Noun (คำนาม) แปลเป็นภาษาอังกฤษว่า example\n
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ความหมาย: ตัวอย่างความหมาย\n
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ตัวอย่างประโยค: ตัวอย่างการใช้ในประโยค<|im_end|>
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```
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The Qwen2 format consists of three main components:
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- **system**: Defines the AI assistant's role and characteristics
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- **user**: Contains the translation query or question (in Thai or English)
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- **assistant**: Provides the structured response including:
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- Word type/category
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- English translation
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- Definition
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- Example sentences (when available)
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- Synonyms (when available)
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- Antonyms (when available)
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- Related words (when available)
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- Classifiers (when available)
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## Example Dataset
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Here is an example of how the dataset is structured:
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```json
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{"instruction": "Please translate 'a' into Thai", "output": "คำว่า 'a' เป็นคำประเภท Determiner แปลเป็นภาษาไทยว่า 'หนึ่ง (คำนำหน้าคำนามเพื่อแสดงว่าคำนามนั้นๆ ไม่ชี้เฉพาะ)'"}
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```
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```text
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<|im_start|>system\nคุณคือผู้ช่วยตอบคำถามที่ฉลาดและซื่อสัตย์<|im_end|>\n<|im_start|>user\nคำว่า 'ดังกล่าวข้างต้น' สามารถใช้ในประโยคอย่างไรได้บ้าง<|im_end|>\n<|im_start|>assistant\nคำว่า 'ดังกล่าวข้างต้น' เป็นคำประเภท Pronoun (คำสรรพนาม) แปลเป็นภาษาอังกฤษว่า abovementioned\nคำที่มีความหมายเหมือนกัน: ดังกล่าว\nตัวอย่างประโยค: หน่วยงานของเราสามารถรับบทบาทได้เป็นอย่างดี ตามสภาพความพร้อมด้านต่างๆ ดังกล่าวข้างต้น<|im_end|>
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```
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