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Clear out junk files and repair common Windows errorsFree Scan →Scan for outdated or missing drivers - takes under a minuteDriver Scan →Repair Windows errors before they cause bigger problemsFix Now →Contexto ranks each guess by its semantic proximity to the hidden word: rank 1 is the answer, and smaller numbers mean a closer position in the game’s ordering. The rank is not a spelling score or a percentage. The broad idea resembles embedding-based similarity, but the exact model and calculation used by the original game at contexto.me have not been verified in publicly readable primary material.
What a Contexto rank tells you
Your number is a position in an ordering of guesses by closeness to the target. Rank 1 identifies the hidden word. A guess with a smaller rank is closer in that ordering than one with a larger rank.
Read the rank as an ordinal clue, not a measurement on a linear scale. A move of a few hundred places does not correspond to a fixed amount of semantic improvement, and the available sources do not establish a calibrated percentage for the original game.
Why a word can be close without being a synonym
Embedding-based word similarity represents words as numerical vectors derived from patterns of language use. Comparing those vectors can place words near one another because they appear in similar contexts, even when their definitions differ. A ranked game can use a guess’s position in such an ordering as feedback.
Do these 3 things before closing this tab:
1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsThat kind of proximity is about patterns of use, not a guarantee that two words mean the same thing. Words can be associated through the situations or sentences in which people use them; even opposites can occur in similar contexts. This is a general limitation of distributional similarity, documented in the editorial policy of the independent site contexto.us.com, rather than a verified, measured behavior of contexto.me.
What is—and is not—known about the original game’s AI
The exact embedding model, vocabulary, and similarity calculation used by the original game at contexto.me have not been verified in accessible primary documentation. It is therefore reasonable to use embeddings as a high-level way to understand semantic ranking, but not to claim a particular model, vocabulary size, or vector dimension for the original game.
Rank #2
A third-party solver reports an API endpoint at https://api.contexto.me/machado/en/game/{game_id}/{word} whose response includes a distance value used to derive the displayed rank. The solver also cautions that its own GloVe model does not perfectly match the game’s internal embedding data. This is evidence about that solver’s interaction with the game, not confirmation of the original game’s model or exact similarity metric. See the solver’s discussion at its project page.
Do not confuse Contexto namesakes
Several independent sites use the Contexto name and describe different implementations. The site contexto.us.com says its game is independent and not affiliated with contexto.me; it describes a 70,000-word vocabulary, while its editorial policy says its own ranking uses a precomputed, publicly available 300-dimensional embedding model. Separately, contextogame.online describes a 99,949-word table of 50-dimensional GloVe vectors and cosine similarity. These details conflict and belong to those independent sites, not to the original contexto.me game.
Consequently, a model label or vocabulary figure found on a namesake’s page should not be applied to the original game without documentation from its operator. The distinction matters because matching branding does not establish shared code, data, or ranking behavior.
Quick Recap
How to use the ranking while you play
- Use it to compare direction, not distance: a lower rank is a closer position, but the size of the numerical change is not a fixed semantic unit.
- Think beyond synonyms: when a guess is unexpectedly close, consider shared usage settings, associated ideas, or common phrases, rather than only dictionary definitions.
- Treat odd associations as clues, not proof: a close rank does not establish that two words are equivalent or even closely related in ordinary conversation.
- Do not substitute an outside model for the game: external embeddings can offer a way to explore associations, but the third-party solver notes that its model does not perfectly align with the game’s internal data.
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