# Missing Word Position in Kazakh Sentences

*English translation by SOTA – AI Community of the Russian original. Licensed CC BY-NC-SA 4.0, like the original. Organisers who would like this translation removed can email sota.ai.community@gmail.com.*

*Contest 4 (29 June 2025) of the Kazakhstan IOAI Team Selection Test (Отборочные на IOAI), 2025. This is the Overview tab of the Kaggle competition "TST Day4 Upsolving", the host's public upsolving copy of the contest, open from 29 June to 15 July 2025. Its subtitle reads: "Determine at which place in a Kazakh sentence a word is missing." Original: [kaggle.com/competitions/tst-day-4-upsolving](https://www.kaggle.com/competitions/tst-day-4-upsolving). The Data tab is translated in a separate file. The example sentences are in Kazakh; their English meaning is given in square brackets.*

## Overview

### 📝 Task description:

In this competition participants are given sentences in the Kazakh language from which **one word has been removed**. 

#### Task:

You are given sentences in Kazakh from which one word has been removed. Your task is to predict the **index (position)** at which this missing word stood. Indexing starts from zero.
### Using pretrained models is allowed

## Description

### 📝 Description:

Kazakh is a language with a rich grammar and a flexible word order, which makes it particularly interesting for natural language processing tasks. In this competition participants are asked to solve a task on understanding sentence structure: **determine at which place in the sentence a word was removed**.

#### Example:

**Original sentence:**
`Мен дүкенге барып келдім.` [I went to the shop and came back.]
**After removal:**
`Мен барып келдім.` [I went and came back.]
**Target value:**
`1`, because the word `"дүкенге"` [to the shop] was in second place (index 1).

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### Why does this matter?

This task assesses how well a model is able to understand:

* the syntax of the Kazakh language,
* the logical order of words,
* the semantic continuity of a text.

It is also a useful step towards training language models in Kazakh, especially when resources are limited.

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## Evaluation

## 🧪 Evaluation

### 📊 Main metric: `Accuracy`

This competition uses the **Accuracy** metric to evaluate participants' solutions. This means that a prediction is counted as correct if the **position of the missing word (an integer)** matches the correct one.

### 📌 Definition:

$$
\text{Accuracy} = \frac{\text{Number of correct predictions}}{\text{Total number of examples}}
$$

For example, if out of 1000 sentences the model correctly identified the position of the missing word in 873 of them, then:

$$
\text{Accuracy} = 87.3\%
$$

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