README.md

metadata

license: mit
task_categories:
  - text-classification
language:
  - zh
tags:
  - code
size_categories:
  - 100M<n<1B
model-index:
  - name: AutoModel
    results:
      - task:
          type: vqa
          name: Visual Question Answering
        dataset:
          type: synthetic-dataset
          name: Synthetic Multimodal Dataset
          split: test
        metrics:
          - type: accuracy
            value: 85
pipeline_tag: question-answering
model_index:
  - name: AutoModel
    results:
      - task:
          type: vqa
          name: Visual Question Answering
        dataset:
          type: synthetdataset
          name: Synthetic Multimodal Dataset
          config: default
          split: test
          revision: main
        metrics:
          - type: accuracy
            value: 85
            name: VQA Accuracy
      - task:
          type: automatspeerecognition
          name: Automatic Speech Recognition
        dataset:
          type: synthetdataset
          name: Synthetic Multimodal Dataset
          config: default
          split: test
          revision: main
        metrics:
          - type: wer
            value: 15.3
            name: Test WER
      - task:
          type: captioning
          name: Image Captioning
        dataset:
          type: synthetdataset
          name: Synthetic Multimodal Dataset
          config: default
          split: test
          revision: main
        metrics:
          - type: bleu
            value: 27.5
            name: BL4
            model-index: null
  - name: Evolutionary Multi-Modal Model
    results:
      - task:
          type: vqa
          name: Visual Question Answering
        dataset:
          type: synthetic-dataset
          name: Synthetic Multimodal Dataset
          split: test
        metrics:
          - type: accuracy
            value: 85
            pipeline_tag: audio-text-to-text

-- 2nd International Chinese Word Segmentation Bakeoff - Data Release Release 1, 2005-11-18

• Introduction

This directory contains the training, test, and gold-standard data used in the 2nd International Chinese Word Segmentation Bakeoff. Also included is the script used to score the results submitted by the bakeoff participants and the simple segmenter used to generate the baseline and topline data.

• File List

gold/ Contains the gold standard segmentation of the test data along with the training data word lists.

scripts/ Contains the scoring script and simple segmenter.

testing/ Contains the unsegmented test data.

training/ Contains the segmented training data.

doc/ Contains the instructions used in the bakeoff.

• Encoding Issues

Files with the extension ".utf8" are encoded in UTF-8 Unicode.

Files with the extension ".txt" are encoded as follows:

as_ Big Five (CP950) hk_ Big Five/HKSCS msr_ EUC-CN (CP936) pku_ EUC-CN (CP936)

EUC-CN is often called "GB" or "GB2312" encoding, though technically GB2312 is a character set, not a character encoding.

• Scoring

The script 'score' is used to generate compare two segmentations. The script takes three arguments:

1. The training set word list
2. The gold standard segmentation
3. The segmented test file

You must not mix character encodings when invoking the scoring script. For example:

% perl scripts/score gold/cityu_training_words.utf8
gold/cityu_test_gold.utf8 test_segmentation.utf8 > score.ut8

• Licensing

The corpora have been made available by the providers for the purposes of this competition only. By downloading the training and testing corpora, you agree that you will not use these corpora for any other purpose than as material for this competition. Petitions to use the data for any other purpose MUST be directed to the original providers of the data. Neither SIGHAN nor the ACL will assume any liability for a participant's misuse of the data.

• Questions?

Questions or comments about these data can be sent to Tom Emerson, [email protected].