[Eval] Chinese lantern riddles (openai#1176)

# Thank you for contributing an eval! ♥️

🚨 Please make sure your PR follows these guidelines, **failure to follow
the guidelines below will result in the PR being closed automatically**.
Note that even if the criteria are met, that does not guarantee the PR
will be merged nor GPT-4 access be granted. 🚨

**PLEASE READ THIS**:

In order for a PR to be merged, it must fail on GPT-4. We are aware that
right now, users do not have access, so you will not be able to tell if
the eval fails or not. Please run your eval with GPT-3.5-Turbo, but keep
in mind as we run the eval, if GPT-4 gets higher than 90% on the eval,
we will likely reject it since GPT-4 is already capable of completing
the task.

We plan to roll out a way for users submitting evals to see the eval
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eval count is 15 samples, we hope this makes it easier to create and
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files, so please make sure that you move the JSON file to Git LFS before
submitting a PR. Details on how to use Git LFS are available
[here](https://git-lfs.com).

## Eval details 📑

### Eval name

chinese-lantern-riddles

### Eval description

This evaluation tests the model's performance in solving Chinese lantern
riddles, which are based on the shape, pronunciation, and meaning of
Chinese characters.

### What makes this a useful eval?

Lantern riddles are a traditional Chinese festive activity that involves
multiple participants guessing riddles together. Apart from being a part
of festival celebrations, lantern riddles can also serve as an
educational tool to help Chinese language learners enhance their
vocabulary and language reasoning. Through the process of unraveling the
riddles, students can also develop their logical thinking and reasoning
skills, as well as nurture their imagination and creativity. Lantern
riddles can also spark students' interest in language learning and make
the learning experience more enjoyable.

Although LLMs are able to some extent to decompose Chinese characters
into parts, as mentioned in openai#511, they still face challenges when it
comes to solving riddles. In most cases, GPT 3.5 cannot reason correctly
about the structure of Chinese characters. For instance, the riddle
"上下一体（打一字）" can be interpreted as a combination ("一体") of "上" and "下",
resulting in the answer "卡". However, GPT 3.5 gives the wrong answer,
"升", with a reason that makes no sense. A similar situation occurs when
GPT 3.5 reasons about the pronunciation of Chinese characters, with one
of its explanations stating that the pronunciation of "盼（pàn）" is
similar to the pronunciation of "俄（é）", which is entirely incorrect.
However, on the positive side, GPT 3.5 shows good performance when a
riddle only encodes meaning and does not require reasoning about the
structure and pronunciation.

## Criteria for a good eval ✅

Below are some of the criteria we look for in a good eval. In general,
we are seeking cases where the model does not do a good job despite
being capable of generating a good response (note that there are some
things large language models cannot do, so those would not make good
evals).

Your eval should be:

- [x] Thematically consistent: The eval should be thematically
consistent. We'd like to see a number of prompts all demonstrating some
particular failure mode. For example, we can create an eval on cases
where the model fails to reason about the physical world.
- [x] Contains failures where a human can do the task, but either GPT-4
or GPT-3.5-Turbo could not.
- [x] Includes good signal around what is the right behavior. This means
either a correct answer for `Basic` evals or the `Fact` Model-graded
eval, or an exhaustive rubric for evaluating answers for the `Criteria`
Model-graded eval.
- [x] **Include at least 15 high-quality examples.**

If there is anything else that makes your eval worth including, please
document it below.

### Unique eval value

> Insert what makes your eval high quality that was not mentioned above.
(Not required)

## Eval structure 🏗️

Your eval should

- [x] Check that your data is in `evals/registry/data/{name}`
- [x] Check that your YAML is registered at
`evals/registry/evals/{name}.yaml`
- [x] Ensure you have the right to use the data you submit via this eval

(For now, we will only be approving evals that use one of the existing
eval classes. You may still write custom eval classes for your own
cases, and we may consider merging them in the future.)

## Final checklist 👀

### Submission agreement

By contributing to Evals, you are agreeing to make your evaluation logic
and data under the same MIT license as this repository. You must have
adequate rights to upload any data used in an Eval. OpenAI reserves the
right to use this data in future service improvements to our product.
Contributions to OpenAI Evals will be subject to our usual Usage
Policies (<https://platform.openai.com/docs/usage-policies>).

- [x] I agree that my submission will be made available under an MIT
license and complies with OpenAI's usage policies.

### Email address validation

If your submission is accepted, we will be granting GPT-4 access to a
limited number of contributors. Access will be given to the email
address associated with the commits on the merged pull request.

- [x] I acknowledge that GPT-4 access will only be granted, if
applicable, to the email address used for my merged pull request.

### Limited availability acknowledgment

We know that you might be excited to contribute to OpenAI's mission,
help improve our models, and gain access to GPT-4. However, due to the
requirements mentioned above and the high volume of submissions, we will
not be able to accept all submissions and thus not grant everyone who
opens a PR GPT-4 access. We know this is disappointing, but we hope to
set the right expectation before you open this PR.

- [x] I understand that opening a PR, even if it meets the requirements
above, does not guarantee the PR will be merged nor GPT-4 access be
granted.

### Submit eval

- [x] I have filled out all required fields of this form
- [x] I have used **Git LFS** for the Eval JSON data
- [ ] (Ignore if not submitting code) I have run `pip install
pre-commit; pre-commit install` and have verified that `black`, `isort`,
and `autoflake` are running when I commit and push

Failure to fill out all required fields will result in the PR being
closed.

### Eval JSON data

Since we are using Git LFS, we are asking eval submitters to add in as
many Eval Samples (at least 5) from their contribution here:

<details>
  <summary>View evals in JSON</summary>

  ### Eval
  ```jsonl
{"input": [{"role": "user", "content":
"以下灯谜的谜底是什么(请从汉字的形、音、意等角度考虑)？请给出答案，并给出依据。\n一撇（打一字）。"}], "ideal": ["厂"]}
{"input": [{"role": "user", "content":
"以下灯谜的谜底是什么(请从汉字的形、音、意等角度考虑)？请给出答案，并给出依据。\n内里有人（打一字）。"}], "ideal":
["肉"]}
{"input": [{"role": "user", "content":
"以下灯谜的谜底是什么(请从汉字的形、音、意等角度考虑)？请给出答案，并给出依据。\n二三四五六七八九（打一成语）。"}], "ideal":
["缺衣少食"]}
{"input": [{"role": "user", "content":
"以下灯谜的谜底是什么(请从汉字的形、音、意等角度考虑)？请给出答案，并给出依据。\n谜底在山东（打一国家名）。"}], "ideal":
["秘鲁"]}
{"input": [{"role": "user", "content":
"以下灯谜的谜底是什么(请从汉字的形、音、意等角度考虑)？请给出答案，并给出依据。\n身穿红衣，常年哨放，遇紧急事，往火里闯（打一日常用品）。"}],
"ideal": ["灭火器"]}
  ```
</details>

evals/registry/evals/chinese-lantern-riddles.yaml

@@ -0,0 +1,9 @@
+chinese-lantern-riddles:
+  id: chinese-lantern-riddles.dev.v0
+  description: Test the model's ability to solve Chinese lantern riddles.
+  metrics: [accuracy]
+
+chinese-lantern-riddles.dev.v0:
+  class: evals.elsuite.basic.includes:Includes
+  args:
+    samples_jsonl: chinese-lantern-riddles/samples.jsonl