Skip to content
Install MCP

Technology

Stanford NLP

Last fetched

Stanford NLP is a technology in WhisperGraph's PredictLeads-derived TECHNOLOGY corpus, categorized under development, with a published adopter count of 118 hostnames.

Profile

Category
development
Broader grouping
intelligence and analytics, programming
Published adopter count
118
Vendor
stanford.edu

Stanford NLP is a suite of natural language processing tools developed by the Stanford Natural Language Processing Group. It provides various functionalities such as part-of-speech tagging, named entity recognition, parsing, and sentiment analysis, among others. The tools are designed to help researchers and developers work with human language data effectively.

Vendor site: https://nlp.stanford.edu/

Sample adopters

20 hostnames WhisperGraph observed running Stanford NLP, a sample of the 118 published adopters.

Hosting concentration

The networks announcing the IP addresses of a sample of 20 Stanford NLP adopters, not of all 118 published adopters. A hostname counts once per network.

Related pages

Pivot from Stanford NLP into its category and the vendor behind it.

Queries

Resolves the slug's technology-name candidate(s) and projects the winner's fields.


MATCH (t:TECHNOLOGY)
WHERE t.name =~ $pattern
WITH t ORDER BY t.adopterCount DESC, t.name ASC
WITH collect(t)[0] AS winner, count(t) AS candidates
RETURN winner.name AS name,
       winner.description AS description,
       winner.category AS category,
       winner.parentCategories AS parentCategories,
       winner.adopterCount AS adopterCount,
       winner.url AS url,
       winner.vendorApex AS vendorApex,
       candidates
Run yourself →

Reads a 20-host adopter sample and the ASNs announcing its IP addresses.


MATCH (:TECHNOLOGY {name: $name})<-[:RUNS_TECHNOLOGY]-(h:HOSTNAME)
WITH h LIMIT 20
OPTIONAL MATCH (h)-[:RESOLVES_TO]->(:IPV4)-[:ANNOUNCED_BY]->(ap:ANNOUNCED_PREFIX)
OPTIONAL MATCH (a:ASN)-[:ROUTES]->(ap) WHERE a.name IS NOT NULL
RETURN h.name AS host, a.name AS asn
LIMIT 200
Run yourself →

Or query Whisper from your own LLM workflow via the Whisper MCP server.