Recognition
15 pages filed under Inference › Recognition. A term is a word of the business with its definition, its aliases and the words it relates to.
| Term | aliases | First line | Links |
|---|---|---|---|
| Alias | other name, alternative name | Another name of an entity, declared under aliases in the frontmatter of its note. An alias enters the dictionary with the title and is recognised the same way, compared without regard to case, accents or the plural; it weighs 4 in the search index where the title weighs 5. An alias that another entity carries as its title or alias makes the two homonyms. | 60 |
| Candidate expression | candidate term, term candidate, recurring expression | An expression of one to four words that the keyword discovery kept because it recurs without a note: at least three occurrences in two distinct files, neither starting nor ending with a stopword, not made only of digits, not shorter than three characters, absent from the dictionary and from the rejected terms of the lock. Each candidate is scored by its C-value times its inverse document frequency; from inference.candidate_score, 4.0 by default, it yields W-TERM-UNDEFINED, and above the publication threshold it gets a keyword page. The candidates are listed under candidates.terms of the model with their score, counts and contexts. | 81 |
| Comparison form | normalised form, normalized form | The shape in which two texts are compared: lower-cased, accents stripped, apostrophes unified, each word singularised by the suffix rules of the language pack. "Keyword Page", "keyword pages" and "keyword page" have one comparison form and are one term. Titles and aliases enter the dictionary in this form, stopwords are compared in it, a candidate expression is grouped by it, the search index stores every word with it, and the twin resources comparison reads texts in it. Hyphens and apostrophes stay part of a word. | 61 |
| Dictionary | recognition dictionary | The list of the words the occurrence scan looks for: the titles and aliases of every entity of a locale, keyed by their comparison form, one dictionary per locale of the corpus. Glossary sources come first, so that their titles win when a form names several entities; a stopword never enters it, nor a form shorter than three characters unless inference.short_terms allows it; a form shared by several entities is flagged as a homonym. The dictionary is built once per build, after typing and contract import, and before the scan. | 75 |
| Homonym | homonyms, shared form | Two entities whose title or alias share one comparison form: a term and a business object both called "Source", or two terms whose aliases meet. The tool keeps both, reports I-TERM-HOMONYM with the form and the identifiers, and links every occurrence of the form to each entity at half the confidence it would have with one target, glossary entities first. A ## Not to be confused with section in each note tells the reader which is which; this glossary carries three such pairs on purpose, source, link and index. | 58 |
| Keyword | noteless word, word without a note | A word or expression the discovery kept because it recurs in the corpus without a note defining it: a candidate expression above the publication threshold has a keyword page, whose badge reads "Keyword"; below it, the keyword stays searchable without a page. The to-do page lists the keywords with their counts, so that the glossary owner turns the frequent ones into terms. | 135 |
| Language pack | pack, locale pack | The data that describes a language to the engine, never code: a folder holding pack.yaml (the name of the language, its apostrophes, its collation options, its plural suffix rules, validated by language-pack.schema.json) and stopwords.txt. The engine ships en and fr; a regional variant such as fr-CA uses the pack of its language until a plugin registers a more specific one; another language comes as a pack shipped by a plugin. Each source selects its pack through its BCP 47 locale, which decides its comparison form, its stopwords, its word segmentation and the collation of its index. | 59 |
| Mention | citation, mentions panel entry | One place where another file cites an entity: the citing file, the line, the words around the citation and a link to the passage. A mention is either a link an author wrote, in the text or in the frontmatter, or a recognised word the scan found in a mapped section or in prose; the entity page keeps the two apart, a written link marked "cited", because the first is what someone asserted and the second what the tool inferred, and shows the mentions grouped by citing page as its related pages. The first twenty of an entity are in its page and the rest in its fragment, fragments/<id>.mentions.json, one file per entity and never a global index. | 111 |
| Occurrence | hit, match | One place where a word of the dictionary appears in a file: the file, the line, the position, the words as written, the enclosing section and eighty characters of context. Occurrences are what the tool records first; everything else, links, keyword pages, the to-do page, derives from them. Code blocks, URLs, frontmatter and link targets never yield occurrences. An expression contained in a longer recognised expression is not counted twice ("keyword page" counts once, not also as "page"); two expressions that only partly overlap, such as "build log" and "log summary" in "the build log summary", are each counted. | 126 |
| Publication threshold | threshold, keyword page threshold | The count a candidate expression must reach to get a keyword page: three occurrences in at least two files, inference.keyword_pages in the configuration. Below the threshold the expression stays in the search index but has no page. The discovery has thresholds of its own, inference.ngrams, which decide which expressions are kept at all; the publication threshold decides which of those become pages, and the build summary reports the pages generated and the expressions under the threshold. | 96 |
| Recognised word | recognised mention, marked word | A word of the text of a note that the occurrence scan matched against the dictionary, a title or an alias of an entity, or a recurring expression that the discovery gave a keyword page, read in a paragraph, a list item, a table cell or a quote. On the entity page the build turns it into a link to the page it names, drawn so that it is told apart from a link the author wrote: a dotted underline in the accent when the entity has a note, grey dashes when the expression only has a keyword page and no note; a legend under the text says which is which, and every mark tells on hover which note it leads to or how many passages the expression has. A recognised word carries less weight than a written link: it is what the tool found, not what someone asserted, which is why the three are never drawn alike. A page is marked once per note, on the first occurrence of its word; the later occurrences stay plain text, and the counts of the model do not change. | 64 |
| Section mention | mapped section mention | A recognised word read in a section whose heading the profile maps to a relation: an object named under ## Objects of a screen is accessed by it, a rule under ## Rules constrains it, a note under ## Affects of a decision is affected by it. The section decides the relation, so the link is typed on the first rung and carries the section_mention confidence of 0.70, above a word read in prose. Headings are matched without regard to case or accents, in the language of the source. | 17 |
| Stopword | stop word, stopwords | A word the recognition sets aside: it never enters the dictionary as a title or an alias, a phrase made only of stopwords is never a term, and a candidate expression never starts or ends with one. The defaults come from the language pack of the source, stopwords.txt; inference.stopwords adds files of the project, one word per line, # opening a comment. Stopwords are compared in the same comparison form as terms. A default stopword names nothing on its own in any corpus: an article, a pronoun, a form of an auxiliary or light verb, an adverb of prose, a numeral, a noun that only counts or places; a word that could be a business term somewhere, or that ends a technical compound, is left to the project's own files. | 65 |
| Term | glossary term | A note of a glossary source: the H1 is the term, the first paragraph its definition, aliases its other names and broader the term it specialises. Every title and alias of a term enters the dictionary first, so that its occurrences in every other note link to it; a term never cited yields W-TERM-UNUSED, and a form it shares with another entity makes them homonyms. A term is short and exact; a ## Not to be confused with section settles a homonym. | 85 |
| Word confidence | keyword confidence, candidate confidence, suspected noise | A value between 0 and 1 that says how much a candidate expression looks like a term of the corpus rather than a word of its own prose. Counts alone do not tell them apart, an adverb and a business object both reaching eighty occurrences; the shape of the distribution does. The confidence is the product of five signals read from the corpus alone, in the same pass as the score, without learning: the spread, the share of the files holding the expression, penalised beyond one half; the burst, its occurrences per file, penalised under one and a half from five files; the position, a bonus for the appearances in a heading, a written link or the frontmatter; the neighbourhood, a bonus when a defined term accompanies it in a frequent expression; the morphology, a soft penalty when a word ends like an inflected form of the language pack, suffixes.txt. A plain term of the subject scores 0.72, a word met once in every file 0.36, a word present in every file of the corpus 0. The publication threshold reads it as inference.keyword_pages.min_confidence, one half by default: under it the expression is suspected noise, gets no keyword page and no mark in the text, stays in the search index and is listed, with its reason, on the to-do page of the site, where a call invites to add it to the project's stopwords. The model carries the confidence, its signals and its penalties on every candidate, and the confidence among the attributes of every keyword page. | 43 |
15 recognition of 15 — pagination by twenty. The Links column counts the related pages, which brings the most central recognition of the journey to the top.