car17v2.0-doc2query.template

# Anserini: Regressions for [CAR17](http://trec-car.cs.unh.edu/) (v2.0) + doc2query

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), with doc2query expansions, as proposed in the following paper:

+ Rodrigo Nogueira, Wei Yang, Jimmy Lin, Kyunghyun Cho. [Document Expansion by Query Prediction.](https://arxiv.org/abs/1904.08375) _arxiv:1904.08375_

These experiments are integrated into Anserini's regression testing framework.
For more complete instructions on how to run end-to-end experiments, refer to [this page](experiments-doc2query.md).

The exact configurations for these regressions are stored in [this YAML file](../src/main/resources/regression/car17v2.0-doc2query.yaml).
Note that this page is automatically generated from [this template](../src/main/resources/docgen/templates/car17v2.0-doc2query.template) as part of Anserini's regression pipeline, so do not modify this page directly; modify the template instead.

## Indexing

Typical indexing command:

```
${index_cmds}
```

The directory `/path/to/car17v2.0-doc2query` should be the root directory of Complex Answer Retrieval (CAR) paragraph corpus (v2.0) that has been augmented with the doc2query expansions, i.e., `collection_jsonl_expanded_topk10/` as described in [this page](experiments-doc2query.md).

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

## Retrieval

The "benchmarkY1-test" topics and qrels (v2.0) are stored in [`src/main/resources/topics-and-qrels/`](../src/main/resources/topics-and-qrels/), downloaded from [the CAR website](http://trec-car.cs.unh.edu/datareleases/):

+ [`topics.car17v2.0.benchmarkY1test.txt`](../src/main/resources/topics-and-qrels/topics.car17v2.0.benchmarkY1test.txt)
+ [`qrels.car17v2.0.benchmarkY1test.txt`](../src/main/resources/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 replicate the following results:

${effectiveness}