Parent-child document retrieval in Prompt Engineering / GenAI - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Understanding Parent-Child Document Relationships

In a parent-child document retrieval system, what is the main purpose of establishing a parent-child relationship between documents?

A To randomly assign documents to unrelated categories

B To merge all documents into a single flat list for faster search

C To prevent any document from being indexed in the system

D To enable efficient retrieval of child documents based on parent document queries

💡 Hint

Think about how grouping related documents helps in searching.

Parent-child relationships allow the system to retrieve child documents when querying the parent, improving search relevance and structure.

❓ Predict Output

intermediate

Output of Parent-Child Query in Elasticsearch

Given the following Elasticsearch query to find child documents with a parent of type 'article' having title 'AI Basics', what is the expected output count?

Prompt Engineering / GenAI

POST /my_index/_search
{
  "query": {
    "has_parent": {
      "parent_type": "article",
      "query": {
        "match": { "title": "AI Basics" }
      }
    }
  }
}

A Number of child documents whose parent article's title matches 'AI Basics'

B Number of parent documents with title 'AI Basics' only

C All documents in the index regardless of parent-child relation

D Zero, because 'has_parent' queries are invalid

💡 Hint

Focus on what 'has_parent' query does in Elasticsearch.

'has_parent' returns child documents whose parent matches the query condition, so output count is child docs linked to parents titled 'AI Basics'.

❓ Model Choice

advanced

Choosing the Best Model for Parent-Child Document Retrieval

Which model architecture is best suited for learning hierarchical relationships in parent-child document retrieval tasks?

A Recurrent Neural Networks (RNNs) without attention mechanisms

B Graph Neural Networks (GNNs) that model document nodes and edges

C Convolutional Neural Networks (CNNs) designed for image data

D Simple feedforward neural networks ignoring document structure

💡 Hint

Consider models that can represent relationships between entities.

GNNs naturally model nodes and edges, making them ideal for hierarchical parent-child document relationships.

❓ Metrics

advanced

Evaluating Retrieval Performance for Parent-Child Queries

Which metric best measures the quality of retrieving child documents given a parent document query in a parent-child retrieval system?

A Mean Average Precision (MAP) to evaluate ranking quality of retrieved child documents

B Root Mean Squared Error (RMSE) used for regression tasks

C BLEU score used for machine translation quality

D Confusion matrix used for classification accuracy

💡 Hint

Think about metrics that evaluate ranked retrieval results.

MAP measures how well the system ranks relevant child documents higher, which is key in retrieval tasks.

🔧 Debug

expert

Debugging a Parent-Child Retrieval Query Returning No Results

You run a parent-child query in your system but get zero results, even though you know matching documents exist. Which is the most likely cause?

A The system automatically merges parent and child documents, so separate queries are invalid

B The query syntax is correct but the documents have no fields

C The parent and child documents are indexed in different indices without a proper join setup

D The child documents are always returned regardless of parent query

💡 Hint

Consider how parent-child relationships depend on indexing structure.

Parent-child queries require both document types in the same index with join relationships; separate indices cause no matches.

Practice

1. What is the main purpose of parent-child document retrieval in GenAI systems?

easy

A. To find related documents where one is the parent and others are children

B. To sort documents alphabetically

C. To delete duplicate documents automatically

D. To translate documents into different languages

Solution

1. Step 1: Understand parent-child relationship

   Parent-child document retrieval means finding documents linked by a hierarchical relationship, where one document is the parent and others are its children.

2. Step 2: Identify retrieval goal

   The goal is to retrieve documents that are connected in this way, not just any documents or unrelated tasks like sorting or translating.

3. Final Answer:

   To find related documents where one is the parent and others are children -> Option A

4. Quick Check:

   Parent-child retrieval = find related hierarchical documents [OK]

Hint: Think hierarchy: parent document with linked child documents [OK]

Common Mistakes:

• Confusing retrieval with sorting or translation
• Ignoring the hierarchical link between documents
• Assuming it deletes or modifies documents

2. Which of the following is the correct syntax to query child documents given a parent ID in a GenAI retrieval system?

easy

A. query = {"parent": "12345"}

B. query = {"child_of": "12345"}

C. query = {"parent_id": "12345"}

D. query = {"child_id": "12345"}

Solution

1. Step 1: Identify correct key for parent ID

   In GenAI retrieval, the key to specify parent document ID for child retrieval is usually "parent_id".

2. Step 2: Check other options for correctness

   Options like "child_of", "parent", or "child_id" are not standard or correct keys for this query.

3. Final Answer:

   query = {"parent_id": "12345"} -> Option C

4. Quick Check:

   Use "parent_id" key to query children [OK]

Hint: Look for "parent_id" key to find children documents [OK]

Common Mistakes:

• Using incorrect keys like "child_of" or "child_id"
• Confusing parent and child identifiers
• Omitting quotes around keys or values

3. Given the following code snippet for retrieving child documents, what will be the output if the parent ID has two children with IDs 'c1' and 'c2'?

parent_id = 'p123'
children = retrieve_children(parent_id)
print(children)

medium

A. ['c1', 'c2']

B. ['p123']

C. []

D. Error: retrieve_children not defined

Solution

1. Step 1: Understand function purpose

   The function retrieve_children(parent_id) is designed to return a list of child document IDs for the given parent ID.

2. Step 2: Analyze given data

   Since the parent ID 'p123' has two children with IDs 'c1' and 'c2', the function should return these IDs in a list.

3. Final Answer:

   ['c1', 'c2'] -> Option A

4. Quick Check:

   retrieve_children returns child IDs list [OK]

Hint: Function returns list of children IDs for given parent [OK]

Common Mistakes:

• Assuming it returns parent ID instead of children
• Expecting empty list when children exist
• Confusing function name or missing definition

4. You have this code snippet to retrieve parent documents but it raises an error:

def get_parent(child_id):
    return retrieve_parent(child_id)

print(get_parent('c123'))

What is the most likely cause of the error?

medium

A. The function get_parent has wrong indentation

B. The child_id 'c123' does not exist

C. The print statement syntax is incorrect

D. The function retrieve_parent is not defined or imported

Solution

1. Step 1: Check function usage

   The function get_parent calls retrieve_parent, which must be defined or imported to work.

2. Step 2: Identify error cause

   If retrieve_parent is missing, Python raises a NameError. Other options like child ID missing or print syntax error would cause different errors.

3. Final Answer:

   The function retrieve_parent is not defined or imported -> Option D

4. Quick Check:

   Undefined function causes NameError [OK]

Hint: Check if all called functions are defined or imported [OK]

Common Mistakes:

• Assuming child ID missing causes this error
• Thinking print syntax is wrong
• Ignoring missing function definitions

5. You want to retrieve all child documents for multiple parent documents efficiently. Which approach best applies parent-child document retrieval in GenAI to achieve this?

hard

A. Query each parent ID separately in a loop and combine results

B. Batch query using a list of parent IDs to fetch all children at once

C. Retrieve all documents and filter children manually by parent ID

D. Use a random sampling of documents ignoring parent-child links

Solution

1. Step 1: Understand efficiency in retrieval

   Batch querying multiple parent IDs at once reduces repeated calls and speeds up retrieval.

2. Step 2: Compare approaches

   Querying separately is slower; filtering all documents wastes resources; random sampling ignores relationships.

3. Final Answer:

   Batch query using a list of parent IDs to fetch all children at once -> Option B

4. Quick Check:

   Batch queries improve efficiency in parent-child retrieval [OK]

Hint: Batch queries reduce calls and speed retrieval [OK]

Common Mistakes:

• Querying parents one by one causing slow performance
• Filtering all documents instead of targeted retrieval
• Ignoring parent-child relationships in sampling