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resolve()
The entity API that knows when not to answer
resolve() tells your agent which real-world thing a name refers to: Jaguar the cat or the carmaker, Orange the telecom or the French town. Send text and get a stable ID for each mention, from Wikidata, your knowledge graph or your own vocabulary. When the evidence isn't there, it returns “unresolved” with a reason instead of guessing. Try three live agent demos with no sign-up. Free for individual developers: 1,000 credits a month. The pipeline and clients are open source (Apache-2.0).
Hi Product Hunt, I'm Andrea, co-founder of @wordliftit.
A jaguar swam through the Amazon rainforest. In our demo, a search-based agent files that story under automotive news, because the first hit for "jaguar" is Jaguar Cars. Nothing crashes. The wrong fact just moves into the graph, the markup and the agent's memory.
We have spent years linking text to knowledge graphs, and that one decision, "which thing is this?", is where it goes wrong. resolve() is that decision as an API:
Send text and get a stable ID for every mention, from Wikidata by default
When the evidence is thin, it answers "unresolved" and tells you why
Point it at your own knowledge graph or vocabulary and get your own IDs back
You can run three live agent demos right now with no sign-up, and edit the text to test your own cases. A free key gives individual developers 1,000 credits a month. The pipeline and clients are open source.
resolve() was submitted on Product Hunt and earned 7 upvotes and 3 comments, placing #46 on the daily leaderboard. resolve() tells your agent which real-world thing a name refers to: Jaguar the cat or the carmaker, Orange the telecom or the French town. Send text and get a stable ID for each mention, from Wikidata, your knowledge graph or your own vocabulary. When the evidence isn't there, it returns “unresolved” with a reason instead of guessing. Try three live agent demos with no sign-up. Free for individual developers: 1,000 credits a month. The pipeline and clients are open source (Apache-2.0).
On the analytics side, resolve() competes within API, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how resolve() performed against the three products that launched closest to it on the same day.
Who hunted resolve()?
resolve() was hunted by Andrea Volpini. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of resolve() including community comment highlights and product details, visit the product overview.
Andrea Volpini
Hi Product Hunt, I'm Andrea, co-founder of @wordliftit.
A jaguar swam through the Amazon rainforest. In our demo, a search-based agent files that story under automotive news, because the first hit for "jaguar" is Jaguar Cars. Nothing crashes. The wrong fact just moves into the graph, the markup and the agent's memory.
We have spent years linking text to knowledge graphs, and that one decision, "which thing is this?", is where it goes wrong. resolve() is that decision as an API:
Send text and get a stable ID for every mention, from Wikidata by default
When the evidence is thin, it answers "unresolved" and tells you why
Point it at your own knowledge graph or vocabulary and get your own IDs back
You can run three live agent demos right now with no sign-up, and edit the text to test your own cases. A free key gives individual developers 1,000 credits a month. The pipeline and clients are open source.
We also published our benchmark against Google, including the languages where we lose: https://wordlift.io/resolve/#benchmarks
One thing I would love to hear: where would a wrong identity hurt most in what you are building?
Demos: https://wordlift.io/resolve/demos/
Free key: https://wordlift.io/resolve/#access
GitHub: https://github.com/wordlift/content-analysis