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Extract quantities from unstructured text.

Project description

Python library for information extraction of quantities, measurements and their units from unstructured text.


$ pip install quantulum


>>> from quantulum import parser
>>> quants = parser.parse('I want 2 liters of wine')
>>> quants
[Quantity(2, 'litre')]

The Quantity class stores the surface of the original text it was extracted from, as well as the (start, end) positions of the match:

>>> quants[0].surface
u'2 liters'
>>> quants[0].span
(7, 15)

An inline parser that embeds the parsed quantities in the text is also available (especially useful for debugging):

>>> print parser.inline_parse('I want 2 liters of wine')
I want 2 liters {Quantity(2, "litre")} of wine

Units and entities

All units (e.g. litre) and the entities they are associated to (e.g. volume) are reconciled against WikiPedia:

>>> quants[0].unit
Unit(name="litre", entity=Entity("volume"), uri=

>>> quants[0].unit.entity
Entity(name="volume", uri="")

This library includes more than 290 units and 75 entities. It also parses spelled-out numbers, ranges and uncertainties:

>>> parser.parse('I want a gallon of beer')
[Quantity(1, 'gallon')]

>>> parser.parse('The LHC smashes proton beams at 12.8–13.0 TeV')
[Quantity(12.8, "teraelectronvolt"), Quantity(13, "teraelectronvolt")]

>>> quant = parser.parse('The LHC smashes proton beams at 12.9±0.1 TeV')
>>> quant[0].uncertainty

Non standard units usually don’t have a WikiPedia page. The parser will still try to guess their underlying entity based on their dimensionality:

>>> parser.parse('Sound travels at 0.34 km/s')[0].unit
Unit(name="kilometre per second", entity=Entity("speed"), uri=None)


If the parser detects an ambiguity, a classifier based on the WikiPedia pages of the ambiguous units or entities tries to guess the right one:

>>> parser.parse('I spent 20 pounds on this!')
[Quantity(20, "pound sterling")]

>>> parser.parse('It weighs no more than 20 pounds')
[Quantity(20, "pound-mass")]


>>> text = 'The average density of the Earth is about 5.5x10-3 kg/cm³'
>>> parser.parse(text)[0].unit.entity
Entity(name="density", uri=

>>> text = 'The amount of O₂ is 2.98e-4 kg per liter of atmosphere'
>>> parser.parse(text)[0].unit.entity
Entity(name="concentration", uri=


While quantities cannot be manipulated within this library, there are many great options out there:


Soon, you’ll find it here.


See units.json (quantulum/resources/units.json) for the complete list of units and entities.json (quantulum/resources/entities.json) for the complete list of entities. The criteria for adding units have been:

1. the unit has (or is redirected to) a WikiPedia page 1. the unit is in common use (e.g. not the pre-metric Swedish units of measurement).

It’s easy to extend these two files to the units/entities of interest. Here is an example of an entry in entities.json:

    "name": "speed",
    "derived": [{"base": "length", "power": 1}, {"base": "time", "power": -1}],
    "URI": ""
  • name and URI are self explanatory.

  • derived is the dimensionality, a list of dictionaries each having a base (the name of another entity) and a power (an integer, can be negative).

Here is an example of an entry in units.json:

    "name": "metre per second",
    "surfaces": ["metre per second", "meter per second"],
    "entity": "speed",
    "URI": "",
    "derived": [{"base": "metre", "power": 1}, {"base": "second", "power": -1}],
    "symbols": ["mps"]
  • name and URI are self explanatory.

  • surfaces is a list of strings that refer to that unit. The library takes care of plurals, no need to specify them.

  • entity is the name of an entity in entities.json

  • derived follows the same schema as in entities.json, but the base is the name of another unit, not of another entity.

  • symbols is a list of possible symbols and abbreviations for that unit.

All fields are case sensitive.

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