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numbermarked

Numbermarked is a data annotation scheme used in natural language processing to label numeric expressions in text with structured metadata. It enables downstream systems to interpret numbers reliably, beyond plain text.

An annotation typically records attributes such as type (integer, decimal, fraction, percentage, currency, date-time), value, sign,

In practice, numbermarked can be encoded in formats such as JSON, XML, or IOB tagging. For example,

Uses include information extraction, financial analytics, and question answering, where explicit numeric data improves accuracy and

Relation to standards: numbermarked draws on ideas from numeric normalization and unit tagging, and can be

Limitations: language variability, ambiguous units, and privacy concerns when numbers reveal sensitive information. Language coverage and

See also: numeric normalization, unit annotation, named-entity recognition, information extraction.

and
unit,
as
well
as
optional
qualifiers
like
approximate,
range,
or
uncertainty.
The
scheme
supports
both
token-level
and
span-level
annotations.
The
price
is
$19.99
would
be
annotated
with
type
currency,
value
19.99,
and
currency
USD.
A
date
such
as
2024-05-20
would
be
tagged
as
date-time
with
value
2024-05-20.
reasoning.
It
complements
traditional
named-entity
recognition
by
focusing
on
numeric
semantics
and
units.
integrated
with
knowledge
graphs
via
linked
data
representations.
The
approach
emphasizes
the
explicit
representation
of
numerical
content
to
support
cross-domain
data
fusion
and
quantitative
reasoning.
consistency
of
annotation
guidelines
can
affect
interoperability,
requiring
clear
schemas
and
validation
processes.