Text matching

Exact name matching, word-phrase matching, how Chinese, Japanese and Korean text is matched, and why there is no substring search.

The API matches text in two ways. Neither is a substring or similarity search.

Kind	Parameters	Matches
Exact	mark_text, primary_owner_name, owner_name, representative_name, previous_owner_name, and the *_key forms	The whole normalized value, and nothing else
Phrase	mark_text_phrase, owner_name_phrase, representative_name_phrase	Records where the words appear in order, anywhere in the field

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Exact matching

Exact filters normalize your value the same way stored names are normalized (accents removed, punctuation turned into spaces, upper case, legal-form suffixes dropped; see name keys), then compare the whole value.

• mark_text=NOKY finds marks whose text is NOKY, Noky or noky, and not NOKY PLUS.
• owner_name=L'Oréal S.A. finds owners whose key is L OREAL.

Each exact filter takes up to 20 values. The normalized value is cut to 512 characters.

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Phrase matching

mark_text_phrase searches the mark text, its translation and transliteration, and keywords the office assigned to the mark. owner_name_phrase and representative_name_phrase search party names and their translations. Each takes one value of 1 to 200 characters, which must contain at least one letter or digit.

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Latin, Cyrillic and other alphabetic scripts

Text is split into words, and the phrase matches whole words in order. Case does not matter.

mark_text_phrase	Matches	Does not match
nike	NIKE, NIKE AIR, AIR NIKE	UNIKEN, NIKEA
nike air	NIKE AIR, NIKE-AIR, NIKE / AIR MAX	AIR NIKE, NIKEAIR
at&t	AT&T, AT T	ATT

Punctuation between words does not have to match: nike air also finds NIKE-AIR. Accents are not removed for you, so if a mark may be written with and without accents, search both spellings.

Apostrophes are kept inside words, so l'oreal is one word. The API searches both the straight (') and the typographic (’) apostrophe for you.

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Chinese characters

Chinese characters, which Japanese also uses as kanji, are matched as an exact character sequence anywhere in the text. 科技 matches every mark containing those two characters next to each other, such as 华为科技 or 科技之光. For Chinese text a phrase search therefore behaves like a substring search. Japanese hiragana is matched the same way.

A single common character or a two-character word can match hundreds of thousands of records. Narrow it with jurisdiction, a date range or another anchor such as owner_key (see below).

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Korean and katakana

A run of Korean hangul syllables, or of Japanese katakana, counts as one word and is matched like a Latin word: 삼성 matches 삼성 전자 but not 삼성전자. Search the whole word as it is written in the mark, and search the variants you expect.

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No substring search

v1 has no substring, prefix, wildcard, fuzzy, phonetic or similarity search. Word matching is the right behaviour for brand searches in alphabetic scripts: nike should not return UNIKEN. Measured on a sample of about 52 million records, a whole-word search for nike returned 969 records where a substring match returned 3,127; the difference is words that merely contain those four letters.

If you need broader matching for a clearance pre-screen, search the distinctive words of the mark separately, and search known variants and translations. See Clearance pre-screen.

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When a phrase matches too much

A phrase that matches more than 100,000 records gets 422 query-too-broad. Narrow it before retrying:

# 422: 科技 alone matches too many records
--data-urlencode "mark_text_phrase=科技"

# Works: one register and recent filings
--data-urlencode "mark_text_phrase=科技" --data-urlencode "jurisdiction=CN" --data-urlencode "application_date_from=2024-01-01"

# Works: combined with an owner key
--data-urlencode "mark_text_phrase=科技" --data-urlencode "owner_key=腾讯科技 深圳 有限公司" --data-urlencode "jurisdiction=CN"

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When phrase search is unavailable

Phrase filters use full-text indexes. While an index is being rebuilt, or if it fails its health check, requests that use it get 503 search-index-unavailable. Exact filters and all other filters keep working, so a number or mark_text lookup is a good fallback.