car17v2.0.template

# Anserini Regressions: CAR17 (v2.0)

**Models**: various bag-of-words approaches

This page documents regression experiments for the [TREC 2017 Complex Answer Retrieval (CAR)](http://trec-car.cs.unh.edu/) section-level passage retrieval task (v2.0).
The exact configurations for these regressions are stored in [this YAML file](${yaml}).
Note that this page is automatically generated from [this template](${template}) as part of Anserini's regression pipeline, so do not modify this page directly; modify the template instead.

From one of our Waterloo servers (e.g., `orca`), the following command will perform the complete regression, end to end:

```
python src/main/python/run_regression.py --index --verify --search --regression ${test_name}
```

## Indexing

Typical indexing command:

```
${index_cmds}
```

The directory `/path/to/car17v2.0` should be the root directory of Complex Answer Retrieval (CAR) paragraph corpus (v2.0), which can be downloaded [here](http://trec-car.cs.unh.edu/datareleases/).

For additional details, see explanation of [common indexing options](common-indexing-options.md).

## Retrieval

The "benchmarkY1-test" topics and qrels (v2.0) are stored [here](https://github.com/castorini/anserini-tools/tree/master/topics-and-qrels), which is linked to the Anserini repo as a submodule.
They are downloaded from [the CAR website](http://trec-car.cs.unh.edu/datareleases/):

+ [`topics.car17v2.0.benchmarkY1test.txt`](https://github.com/castorini/anserini-tools/tree/master/topics-and-qrels/topics.car17v2.0.benchmarkY1test.txt)
+ [`qrels.car17v2.0.benchmarkY1test.txt`](https://github.com/castorini/anserini-tools/tree/master/topics-and-qrels/qrels.car17v2.0.benchmarkY1test.txt)

Specifically, this is the section-level passage retrieval task with automatic ground truth.

After indexing has completed, you should be able to perform retrieval as follows:

```
${ranking_cmds}
```

Evaluation can be performed using `trec_eval`:

```
${eval_cmds}
```

## Effectiveness

With the above commands, you should be able to reproduce the following results:

${effectiveness}