More on ontologies + wordnet

legal_ontology.md

@@ -12,7 +12,7 @@ Say that you write a law that says
 
 > You have the obligation to pay taxes.
 
-Maybe you link your law to [WordNet](https://wordnet.princeton.edu/) and make sure you have the right sense of "you", "have", "obligation", "pay" and "taxes". Now you can translate it into any other language that has a [linked WordNet](https://github.com/GrammaticalFramework/gf-wordnet#readme) with the same identifiers.
+Maybe you link your law to <wordnet> and make sure you have the right sense of "you", "have", "obligation", "pay" and "taxes". Now you can translate it into any other language that has a [linked WordNet](https://github.com/GrammaticalFramework/gf-wordnet#readme) with the same identifiers.
 
 Now you know that _obligation_ in the sense `06785951` 'a legal agreement specifying a payment or action and the penalty for failure to comply' is translated into Bulgarian as _обвързаност_.
 

ontology.md

@@ -6,8 +6,79 @@ date: "2020-06-17"
 
 Collection of concepts and their relationships, in a machine-readable format.
 
-Kind of like this zettelkasten: here we link concepts to each other. In addition, the _links_ themselves may have types and be the subject or object in another relation, linked by something that itself has a type and can be a subject/object of yet another relation, and so on.
+<sumo> is a big, well-known general ontology.
 
-Contrast with a web of free text, this kind of structure allows for e.g. automated question answering.
+### Taxonomy
 
-(That is just one kind of ontology, there are other designs. I don't know this area very well. But other ontologies seem to contain _axioms_ or _facts_.)
+The basic building block of an ontology is a hierarchy of concepts. Higher nodes represent general concepts, lower nodes more specific. Example:
+
+              Entity
+              /  |  \
+        Biology  …  Geography
+        / | | \ … … / | | \
+     … … … … … … … … … … … … …
+         |                 \
+      Neurology           Europe
+      / | | \            /   |  \
+     … … … … … … … … … … … … … … …
+     |                         |
+    Optic nerve          Heathrow airport
+
+
+Just a tree of arbitrary labels isn't particularly useful. That's why ontologies may have some of the following features.
+
+### Relationships
+
+So far we've seen only taxonomy membership in a strict tree structure.
+* Spice Girls `is-a` Band
+* Wannabe `is-a` Song
+
+But we can also have other _relationships_.
+* Spice Girls `perform` Wannabe
+* Wannabe `year` 1996
+
+Furthermore, the relation links themselves can be the subject or object in another relation.
+* Perform `is-a` Action
+* is-a `is-a` Relation
+
+See [RDF](https://en.wikipedia.org/wiki/Resource_Description_Framework), a data model based on such triples.
+
+### Axioms
+TODO
+
+### Mapping to logic
+TODO
+
+### Mapping to lexical resources
+
+[Niles and Pease (2003)](http://www.adampease.org/professional/Niles-IKE.pdf) map mid-level entries from <sumo> to <wordnet>. WordNet itself has some relations like synonymy and hypernymy, and I'm not quite sure how they work together with the relations of an ontology (TODO: read the whole 2003 paper).
+
+Main point is that a concept in an ontology corresponds to one or more synonym sets in WordNet. Consider a corner of ontology like the following:
+
+                Entity
+                /    \
+          Abstract   Physical
+          / | | \    /    |  \
+      Attribute …  …     …    …
+        / | \
+           Measure
+           /     \
+    TimeMeasure  LengthMeasure
+
+
+The concept `Measure` is mapped to a number of WordNet synonym sets, such as
+* _space_ 00014887 '3-dimensional expanse in which everything is located'
+* _time_ 15160774	'the fourth coordinate that is required (along with three spatial dimensions) to specify a physical event'
+
+And `LengthMeasure` is mapped only to 00014887 _space_.
+
+
+## Ontology extraction
+
+Quote from [Herbelot, 2011](https://web.archive.org/web/20130704143830/http://www.peerpress.de/discoursecpp.pdf)
+
+> [O]ntology extraction — a subfield of natural language processing which, put simply, specialises in producing lists. […] Well-loved ontology extraction tasks include the retrieval of Oscar nominees, chemical reactions and dead presidents. In this kind of research, the machine is asked, for instance, to produce a list of things that are ‘like lorries’ and is expected to duly return (given the current state of the art)  
+>
+>    `truck car motorcycle plane engine hamster.`  
+>
+> Because lorries have wheels and hamsters have too.

sumo.md

@@ -0,0 +1,29 @@
+---
+date: "2020-06-18"
+---
+
+# SUMO
+
+SUMO (Suggested Upper-Merged Ontology) has the approach of _domain_ ontologies and _merge_ ontologies. Example:
+
+* Top level
+```
+            Entity
+            /    \
+      Abstract   Physical
+      / | | \    /    |  \
+  Attribute … … Object … Process
+```
+* Domain ontology
+```
+          AirportsFromAtoK
+           /      |      \
+     <fine-grained distinctions>
+        /    /    |    \     \
+    Arlanda  …    …  Heathrow  …
+
+```
+
+All entries in SUMO are part of a single tree, starting from `Entity`. A domain ontology about airports is linked to the top level ontology, in a distant subtree of physical entities.
+
+TODO: I don't know how the linking works in practice, or if the technical details have any relevance to the scope of CCLAW readings. ([Niles, Pease (2001)](https://dl.acm.org/doi/pdf/10.1145/505168.505170) seems to describe the merging process, read later if interested.)

wordnet.md

@@ -0,0 +1,24 @@
+---
+date: "2020-06-18"
+---
+
+# WordNet
+
+[Princeton WordNet](https://wordnet.princeton.edu/) is a lexical database consisting of _synonym sets_ (synset). Each synset has
+- id
+- part-of-speech (noun, verb or adjective)
+- definition
+- example(s) of use
+
+The word "space" belongs to the following synsets.
+
+* 00028950-__n__ _the unlimited expanse in which everything is located; "they tested his ability to locate objects in space"_
+* 13933399-__n__ _an empty area (usually bounded in some way between things); "the architect left space in front of the building"; "they stopped at an open space in the jungle"; "the space between his teeth"_
+* 08670545-__n__ _an area reserved for some particular purpose; "the laboratory's floor space"_
+* 08517454-__n__ _[astrology] any location outside the Earth's atmosphere; "the astronauts walked in outer space without a tether"; "the first major milestone in space exploration was in 1957, when the USSR's Sputnik 1 orbited the Earth"_
+* 06852240-__n__ _[linguistics, publishing] a blank character used to separate successive words in writing or printing; "he said the space is the most important character in the alphabet"_
+* 15197259-__n__ _[time period] the interval between two times; "it all happened in the space of 10 minutes"_
+* 06401196-__n__ _a blank area; "write your name in the space provided"
+* 06875252-__n__ _[music] one of the areas between or below or above the lines of a musical staff; "the spaces are the notes F-A-C-E"_
+* 04037131-__n__ _[publishing] a block of type without a raised letter; used for spacing between words or sentences_
+* 01992094-__v__ _place at intervals; "Space the interviews so that you have some time between the different candidates"_