Poetry Website Classification API Overview and Use Cases

You need to automatically detect poetry-related websites at scale so you can enforce content policies, enrich signups from literary domains, and audit where your ads appear. By the end of this guide, you’ll have a working request against Klazify’s categorization API, code you can drop into your pipeline, and a plan for caching, batching, handling unknown domains, and mapping results into your own taxonomy.

Why Klazify works uniquely well for poetry-focused classification

Poetry content is nuanced: small presses, literary magazines, community workshops, and writer portfolios often have sparse navigation, long-form text, and infrequent updates. Klazify’s approach aligns with that reality:

• Accurate website categorization using AI: The API analyzes on-page content, not just metadata, which helps reliably recognize poetry and literature themes across homepages, issue archives, and poem pages.
• Global coverage: Poetry is multilingual and regional. Klazify’s ability to analyze content in multiple languages helps you catch poetry domains published outside your primary market.
• Real-time classification: Instead of relying on stale lists, the API classifies current content, so new poetry journals, seasonal calls for submissions, or newly launched author sites can be detected quickly.
• Industry-level categories: Results are mapped to the IAB taxonomy, allowing you to align poetry and broader literature topics with standard ad-tech and brand-safety workflows.
• Simple API integration: A single POST request returns website categories plus signals like logo, social detection, and company metadata you can plug into enrichment flows for presses, journals, and events.
• Compliance and filtering: Poetry and literature sites can be whitelisted for education or library networks while unrelated categories are filtered out, using a consistent categorization backbone.

If your goals include filtering for literature-related content, enriching user or lead profiles that list poetry domains, or auditing ad placement adjacency around literary content, Klazify provides the relevant data in one call.

What you’ll build: classify a domain and act on poetry signals

In this section you’ll:

• Send your first categorization request using the categorize endpoint.
• Parse the response to extract the category path(s), confidence, and auxiliary domain signals.
• Decide how to handle poetry-related results in three scenarios: blocklist/allowlist, enrichment, and ad auditing.

You’ll use the official POST endpoint and the same request shape used in the docs fixture. We’ll also cover caching and unknown-domain handling so your integration scales cleanly.

Send your first request

Endpoint: https://www.klazify.com/api/categorize (POST)
Authentication: Bearer token in the Authorization header
Payload: JSON with a single key "url", set to the URL or domain you want to classify

curl example (docs fixture)

curl -X POST "https://www.klazify.com/api/categorize" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{"url":"https://cbsnews.com"}'

Replace YOUR_API_KEY with your token. The POST body can be any resolvable URL or bare domain, for example a poetry journal or an author’s portfolio. Failed or unreachable calls are not billed. If you’re new to Klazify, you can start with the Starter plan ($39.99/mo) and a 7-day trial.

Python example

import os
import json
import requests
from typing import Dict, Any, List

API_KEY = os.getenv("KLAZIFY_API_KEY", "YOUR_API_KEY")
API_URL = "https://www.klazify.com/api/categorize"

def classify_domain(target_url: str) -> Dict[str, Any]:
headers = {
"Authorization": f"Bearer {API_KEY}",
"Content-Type": "application/json",
}
payload = {"url": target_url}
resp = requests.post(API_URL, headers=headers, json=payload, timeout=25)
resp.raise_for_status()
return resp.json()

def extract_categories(data: Dict[str, Any]) -> List[Dict[str, Any]]:
domain = data.get("domain") or {}
return domain.get("categories") or []

def extract_logo(data: Dict[str, Any]) -> str:
domain = data.get("domain") or {}
return domain.get("logo_url") or ""

def extract_company(data: Dict[str, Any]) -> Dict[str, Any]:
objects = data.get("objects") or {}
return (objects.get("company") or {})

def extract_domain_registration(data: Dict[str, Any]) -> Dict[str, Any]:
return data.get("domain_registration_data") or {}

def is_poetry_adjacent(categories: List[Dict[str, Any]]) -> bool:
# Example matching logic: check for literature/arts branches in the category path.
# Avoid hard-coding exact names; match by presence of known parent segments.
# You can tune this to your taxonomy mapping rules.
signals = [c.get("name","") for c in categories]
return any(seg.startswith("/Arts & Entertainment") or "Books" in seg or "Literature" in seg for seg in signals)

if __name__ == "__main__":
data = classify_domain("https://cbsnews.com")
cats = extract_categories(data)
logo = extract_logo(data)
company = extract_company(data)
whois = extract_domain_registration(data)

print("Categories:")
for c in cats:
print(f" - {c.get('name')} (confidence={c.get('confidence')})")

print("\nLikely poetry-adjacent:", is_poetry_adjacent(cats))
print("\nLogo URL:", logo)
print("\nCompany snapshot:", json.dumps(company, indent=2))
print("\nRegistration data:", json.dumps(whois, indent=2))

Notes:

• The function is_poetry_adjacent shows how to test category paths without naming a specific category string. Tune those checks for your taxonomy.
• Use timeout and standard retry logic in production. Cache successful results by registrable domain to avoid re-calling for every pageview.

Interpreting the response

This is the official example response format. Use it to understand available fields and how you’ll wire them into your pipeline.

{
"domain": {
"categories": [
{
"confidence": 0.92,
"name": "/Computers & Electronics/Consumer Electronics",
"IAB-632-596": "Consumer Electronics/Technology & Computing/Consumer Electronics"
},
{
"confidence": 0.89,
"name": "/Internet & Telecom/Mobile & Wireless/Mobile Phones"
}
],
"social_media": null,
"logo_url": "https://klazify.s3.amazonaws.com/2110787991611585019600ed5fb1d1300.04730104.png"
},
"success": true,
"objects": {
"company": {
"url": "https://www.apple.com/",
"name": "Apple",
"city": "Cupertino",
"stateCode": "CA",
"countryCode": "US",
"employeesRange": "100K+",
"revenue": 274515000000,
"raised": null,
"tags": [
"E-commerce",
"Consumer Electronics",
"Mobile",
"B2C"
],
"tech": [
"omniture_adobe_analytics",
"atlassian_confluence",
"successfactors",
"apache_apex",
"talend",
"oracle_peoplesoft",
"salesforce",
"stripe",
"dell_boomi_atomsphere",
"gigya",
"sage_50cloud",
"quickbooks",
"webmethods",
"apache_tomcat",
"alteryx",
"tibco_rendezvous",
"atlassian_jira",
"..."
]
}
},
"domain_registration_data": {
"domain_age_date": "1987-02-19",
"domain_age_days_ago": "13026",
"domain_expiration_date": "2030-02-20",
"domain_expiration_days_left": "123"
},
"similar_domains": [
"bestbuy.com",
"icloud.com",
"microsoft.com",
"macrumors.com",
"google.com",
"samsung.com",
"twitter.com",
"hp.com",
"bhphotovideo.com",
"dell.com"
]
}

How to use these fields for poetry-focused workflows:

• domain.categories: Each item has a name (category path) and confidence. For poetry use cases, you’ll look for category paths within arts and literature branches of the taxonomy, then apply your action (allow, block, enrich, route).
• IAB mapping: Where present, the IAB-… code maps the detected content to the IAB taxonomy for ad-tech alignment. This lets you keep poetry and literature contexts safe for your creative or educational placements.
• domain.logo_url: Handy for enriching CRM entries for presses, journals, and festivals when a logo is available.
• objects.company: A snapshot of company-level info detected from the URL, useful for lead enrichment or internal entity resolution (e.g., when a literary organization runs multiple subdomains).
• domain_registration_data: Registration timestamps help you score domain maturity, which can factor into trust or data hygiene rules when encountering newly-registered poetry domains.
• similar_domains: Seed discovery for nearby properties you might also want to classify, crawl, or categorize.

Acting on poetry results: three implementation patterns

1) Content filtering and brand safety

Goal: Allow poetry and literature topics while avoiding unrelated or risky contexts. After reading domain.categories, implement a ruleset:

• If category path aligns with your poetry/literature allowlist, mark “context_allowed=true”.
• Else, route to general or restricted inventory depending on your policy.

Persist the allow/block decision keyed by the eTLD+1 (e.g., example.org) with a TTL. For URLs under a large site with mixed content, consider classifying page-level URLs and caching at the path level for high-variance sections.

2) Signup and lead enrichment

Goal: Enrich a new user who signs up with a poetry journal or author site. On signup, call the endpoint with the user’s entered domain, then store:

• Detected category path(s) and confidence to populate an interest/industry field.
• logo_url to add a recognizable avatar for their organization.
• company details (if present) like location and tags to speed up internal routing or approval.

Because enrichment is synchronous to the UX, cache the response and add a fallback policy (e.g., queue for a retry) when the site is temporarily unreachable to avoid slowing the form.

3) Ad placement auditing

Goal: Confirm your ads render near literature/poetry contexts. Capture the page URL where the ad served, classify that URL, and log:

• Category path(s) and confidence at the time of delivery.
• A normalized IAB mapping (when present) for reporting consistency across buys.
• Any similar domains as candidates for inclusion/exclusion updates.

Aggregate the auditing data nightly to ensure your placements match targeting policies for poetry-related content.

Operational details you’ll wish you had up front

Caching

• Cache at the registrable domain (eTLD+1) for domain-level classification. Use URL-level caching only for sites known to host diverse content under the same domain.
• Set a TTL appropriate to your change tolerance. Poetry sites update less frequently than news, so longer TTLs are often fine for domain-level classification.
• Cache negative and retry states separately (e.g., unreachable) with a short TTL so temporary outages don’t hammer the endpoint.

Batching and throughput

• Create a queue for new or unseen domains gathered from logs or signups. Run workers that read from the queue and call the API.
• Apply rate limiting on your side and backoff on HTTP/network errors. If a domain returns unreachable, requeue with exponential delay.
• De-duplicate by normalized domain/URL string before enqueueing to cut redundant calls.

Handling unknown or new domains

• Classify, then assign a provisional policy based on broad parent categories when confidence is low or mapping is sparse.
• Flag newly registered domains (from domain_registration_data) for closer scrutiny in sensitive workflows.
• If social_media is absent and the site is sparse, schedule a recheck after a delay; some poetry sites launch with placeholders before content appears.

Mapping to your taxonomy

• Maintain a mapping table from category path segments (and IAB codes where available) to your internal categories such as “Poetry,” “Literary Magazine,” “Press,” “Author Site.”
• When multiple categories are returned, prioritize by confidence and define tie-breakers (e.g., prefer literature-aligned parents over general arts).
• Log categories and mapping decisions to improve your rules as you see corner cases (e.g., a university department page hosting poetry content).

Reliability and billing notes

• Failed or unreachable calls are not billed, which is helpful when classifying small or intermittently hosted poetry sites.
• Implement retries with jitter and monitor error codes separately from empty or low-confidence results.
• If you need an overview of machine-checkable endpoints related to Klazify, see the MCP page. Direct calls to https://mcp.klazify.com (e.g., GET /mcp) will return 405; use the standard categorize endpoint for classification.

How poetry appears in Klazify’s categories

In production, you’ll look for category paths that fall under arts and literature branches of the taxonomy. Your mapping table should list the parent branches you consider “poetry-adjacent” and assign an action (allowlist, enrich, audit). When an IAB code is provided, include it in reports to align with other ad-tech tools.

Example logic you can adopt:

• If the top category path contains arts/literature segments and confidence ≥ threshold, mark as Poetry Context.
• If multiple categories are returned and only one aligns with literature, prefer that path if its confidence is within X% of the top category.
• Otherwise, mark as General Context and route to safe default handling.

Putting it together: pipeline design

Event sources

• Signups: Parse domains from user-submitted emails or website fields.
• Traffic logs: Extract referrers, landing pages, and ad placement URLs.
• Data syncs: Ingest partner or CRM domains for periodic enrichment.

Normalize and deduplicate

• Normalize URLs (scheme, lowercase host, strip tracking params when allowed).
• Derive registrable domain for domain-level caching and a separate key for URL-level classification where needed.
• Drop duplicates within a configurable time window before enqueueing.

Classify

• POST to the categorize endpoint with timeouts and retry policy.
• Parse domain.categories, logo_url, objects.company, and domain_registration_data.
• Store raw JSON and extracted fields; you’ll want the original for audits.

Decide and act

• Run category mapping to your poetry taxonomy and compute an action decision.
• Cache the decision with a TTL; store a shorter TTL for edge cases or low confidence.
• Emit events for downstream systems (filtering, CRM enrichment, ad QA reports).

Monitor

• Track classification volume, error rates, and decision distributions (how often you hit poetry-adjacent vs general contexts).
• Periodically sample domains for reclassification to confirm stability of poetry-related properties.

Comparison: which fields to use for common poetry workflows

Workflow	Primary fields	Why	Typical action
Content filtering (allow/deny)	domain.categories, confidence, IAB mapping	Category path + confidence drives decisions; IAB supports ad-tech alignment	Allowlist poetry/literature; fallback to general policy on low confidence
Signup enrichment	domain.categories, domain.logo_url, objects.company	Enrich CRM records for journals, presses, and authors	Attach logo, set industry fields, route to poetry team
Ad placement auditing	URL-level categories, IAB mapping	Confirm context at impression time	Report adjacency; adjust inclusion lists
Discovery/expansion	similar_domains	Find related properties to evaluate	Queue for classification and review
Trust and review	domain_registration_data	Identify very new domains for manual checks	Flag for secondary verification

Next steps and where to go deeper

• Create a free account to get an API key and run your first classification against a poetry journal or author site.
• Review the endpoint details and fields in the API documentation and align your taxonomy mapping table.
• If you maintain internal automation around machine-readable capabilities, see the MCP page for high-level guidance and pointers.

Links you’ll need: Register, Documentation, and MCP. You can always start from the homepage as well: https://www.klazify.com and https://www.klazify.com.

FAQ

• How should I set my confidence threshold for poetry detection?

  Start by logging category paths and confidences for a representative sample of poetry and non-poetry domains. Pick a threshold that maximizes precision for your policy. Many teams also keep a buffer zone (e.g., mid-confidence) for manual or delayed review.

• Should I classify at domain or URL level?

  Default to domain-level for most poetry sites (journals, presses, authors). Use URL-level classification for large platforms that host mixed content, and cache results per path for high-variance sections.

• What if a site is unreachable?

  Mark the request as a temporary failure, do not block or enrich solely on that basis, and retry with exponential backoff. Failed or unreachable calls are not billed.

• How do I reconcile IAB mapping with my internal labels?

  Maintain a mapping table from IAB codes and category path segments to your labels (e.g., Poetry, Literary Magazine, Press). Log decisions to refine the mapping as you encounter edge cases.

• Can I try the API before committing?

  Yes. There’s a 7-day trial on the Starter plan ($39.99/mo). Sign up, get an API key, and run classifications in your staging pipeline.

Ready to classify poetry websites and wire the results into your filters, enrichment flows, or ad auditing? Create your account now and get your API key: Register. For endpoint details and field references, see the Documentation.