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DAML (Semantic Web) Ontology of time for describing
temporal content of web pages temporal properties of web pages temporal properties of web services
Maps easily into other temporal theories/ontologies (e.g., Cyc, SUMO, PSL, ...)
Connects easily with various temporal resources
Supports reasoning about time
Integrated with TimeML for annotation and analysis of NL text
Aims of DAML-Time
Examples
Need bookby next
Tuesday
Ships bookswithin five
business days?
Marriage record for ancestor: year
Find birth records for same name,between 15 and 45 years before
E-Commerce:
Genealogy:
Coverage of Temporal Ontology
1. Topological relations
2. Durations
3. Clock and Calendar
4. Temporal Aggregates
5. Deictic Time
6. Vague Temporal Concepts
Time: Topology
intervalinstants
start endinside
x ybefore(x,y)
before is anti-reflexive, anti-symmetric, transitive
start before inside before end
Interval Relations in Terms of before, starts, ends
(A T1,T2)[int-overlaps(T1,T2) <--> [proper-interval(T1) & proper-interval(T2) & (E t2,t3)[ends(t2,T1) & begins(t3,T2) & before(t3,t2) & (A t1)[begins(t1,T1) --> before(t1,t3)] & (A t4)[ends(t4,T2) --> before(t2,t4)]]]]
T1
T2
t2
t3 t4
t1
The Interval Algebra(Allen & Ferguson, 1997)
before
meets
overlaps
starts
equals
during
finishes
Relationsbetweenthis and
start,end, andbefore
Controversial Issuesand What to do about Them
Are the end points of an interval a part of the interval?
Can there be intervals of zero length?
Is an interval of zero length an instant?
==> Avoid these issues; keep ontology silent. (Many problems arise when trying to identify 0-D and 1-D entities)
Is time totally ordered?
Are there points at infinity?
==> Optional extensions with triggers
Total-order() --> (A t1,t2)[before(t1,t2) v t1=t2 v before(t2,t1)]
Events and Time
Temporal ontology is not an ontology of events, e.g., no aspect, event decomposition, etc.
Predicates to interface events with time:
at-time(e,t) during(e,T) time-span-of(T,e)
Or event ontology can provide its own means:
holds(e,t) p(x,t) etc.
Or in temporal ontology, temporal thing that covers both intervals and events.
Events in the Temporal Ontology
Instants InstantEvents Intervals IntervalEvents
EventsTemporalEntities
TemporalThing
IntervalThingsInstantThings
Then temporal predicates are generalized to TemporalThing, InstantThing, IntervalThing
Units of Duration
duration(T, *Second*) = n means interval T is n seconds long
duration(T,*Second*) = 60*duration(T,*Minute*)duration(T,*Minute*) = 60*duration(T,*Hour*)duration(T,*Hour*) = 24*duration(T,*Day*)duration(T,*Day*) = 7*duration(T,*Week*)
duration(T,*Day*) = ??*duration(T,*Month*)
duration(T,*Month*) = 12*duration(T,*Year*)
Duration Descriptions
Interval
DurationDescription: Seconds: Minutes: Hours: Days: Weeks: Months: Years:
durationDescriptionOf
Many equivalent DurationDescriptions
Temporal Arithmetic duration-description(T,y,m,w,d,h,n,s+60) <--> duration-description(T,y,m,w,d,h,n+1,s)
duration-description(T,y,m,w,d,h,n+60,s) <--> duration-description(T,y,m,w,d,h+1,n,s)
duration-description(T,y,m,w,d,h+24,n,s) <--> duration-description(T,y,m,w,d+1,h,n,s)
duration-description(T,y,m,w,d+7,h,n,s) <--> duration-description(T,y,m,w+1,d,h,n,s)
duration-description(T,y,m,w,d+??,h,n,s) <--> duration-description(T,y,m+1,w,d,h,n,s)
duration-description(T,y,m+12,w,d,h,n,s) <--> duration-description(T,y+1,m,w,d,h,n,s)
Canonical description of duration
Concatenation and "Hath"
Hath(n,u,x): n units of type u comprises x
September(x,y) --> Hath(30,*Day*,x)minute(x) --> Hath(60,*Second*,x)
x
u u u u |S|=n
Concatenation(x,S): x is concatenation of intervals in S
Concatenation(T1,{T2,T3}) --> duration(T1,u) = duration(T2,u) + duration(T3,u)
x
S
Clock and Calendar
Time zones: Not geographical regions, but legal entities Property of hours days months years C.E. CE(z) = Common Era in time zone z
Various ways of saying minit(y,n,x) <--> minitFn(n,x) = y <--> clock-int(y,n,*Minute*,x) <--> y is the nth minute in x
A subset of intervals that correspond to clock or calendar designations, e.g., August 2003
Days of the Week
dayofweek(y,n,x) <--> cal-int(y,n,*Day*,x) & (E x1,n1) cal-int(x,n1,*Week*,x1)
dayofweek(d,1,w) <--> Sunday(d,w)
Tuesday(1-Jan-2000) anchors cycle of weeks
Months and Leap Years
cal-int(m,1,*Month*,y) <--> January(m,y)
January(m,y) --> Hath(31,*Day*,m)
leapyear(y) <--> yr(y,n,CE(z)) & 400 | n v [4|n & ~100|n]
February(m,y) & ~leapyear(y) --> Hath(S,28,*Day*,y)
Month as a Unit of Duration
nth day nth day
one month
But: January 31 + 1 month = February 28 January 30 + 1 month = February 28 February 28 + 1 month = March 28 or March 31? January 31 + 2 months = March 31 January 30 + 2 months = March 30
So [January 30 + 1 month] + 1 month =/= January 30 + 2 months
Need months as units of duration since since chargesare often by the month.
Clock and Calendar
weekendday(d,w) <--> Saturday(d,w) v Sunday(d,w)
da(d,4,m) & July(m,y) --> holiday(d,USA)
business-day(d,g) <--> ~(E w)[weekendday(d,w)] & ~holiday(d,g)
Time Stamps
Time Stamps:
time-of(t,y,m,d,h,n,s,z) <--> in-interval(t,secFn(s,minFn(n,hrFn(h,daFn(d,monFn(m,yrFn(y,CE(z))))))))
If t is 4:25:38 pm PDT, January 28, 2003
then time-of(t,2003,1,28,16,25,38,*PDT*)
Mapping onto ISO 8601 standard
Relate to duration descriptions so temporal arithmetic can be done on dates.
Temporal Aggregates
“five business days”
“every third Monday in 2001”
“every morning for the last four years”
“four consecutive Sundays”
“the first nine months of 1997”
“three weekdays after January 10”
“the fourth of six days of voting”
Temporal Aggregates
temporal sequence: set of nonoverlapping instants and/or intervals ordered by before
first(s), nth(s,n)
futurep(p,u) = s <--> (A t)[member(t,s) <--> (E t1,t2)[p(t) & now(t1,u) & begins(t2,t) & before(t1,t2)]] (sequence of all the p’s after now)
Deictic Time
now(t,u): instant/interval t is now in utterance/document u
today(d,u) <--> now(t,u) & in-interval(t,d) & day(d,n,x)
past(t,u) <--> now(t1,u) & before(t,t1)
ago(t,T,u) <--> now(t1,u) & interval-betw(t,t1) = T
Vague Temporal Concepts
Vague Temporal Concepts:
recently, soon, a little while, ....
Where text annotation can help immensely: what durations do people intend?
She had recently [3 mos] bought a laptop.
In recent [5 yrs] years farmers have been enjoying record yields.
The recent [1 wk] computer crash was costly.
Need data on what these terms mean.
Convergence
TimeML(ARDA AQUAINT program)Annotation of NL corpora
Development of algorithmsfor annotation
For QA, MT, etc.
DAML-Time(DARPA DAML program)
Expressing temporalcontent and capabilities
of Web sites and services
Most information on the Webis in natural language
TimeML <--> DAML-Time
Example
Query: I want the latest book by John McCarthy by next Tuesday.
Author: John McCarthy et al.Book: Formalizing Common SenseDate: 1998Price: $24.95
Delivery within 5 business days
Author: John McCarthyBook: LISP 1.5 Date: 1962Price: $16.95
Author: John McCarthy et al.Book: Defending AI ResearchDate: 1996Price: $21.95
Example
Query: I want the latest book by John McCarthy by next Tuesday. Price is no object.
Author: John McCarthy et al.Book: Formalizing Common SenseDate: 1998Price: $24.95
Delivery within 5 business days
Author: John McCarthyBook: LISP 1.5 Date: 1962Price: $16.95
Author: John McCarthy et al.Book: Defending AI ResearchDate: 1996Price: $21.95
TimeML
Annotation of time and events in natural language text.
Time stamping of events.
Ordering of events wrt each other.
Anchoring of deictic temporal expressions.
Identifying signals of temporal information.
Facilitates reasoning about persistence of events.
Creation of TIMEBANK, gold standard of 300 articles.
An Annotation
Delivery within five business days.
<EVENT eid="e1" class="OCCURRENCE" tense=”NONE" aspect="NONE">Delivery</EVENT><MAKEINSTANCE eiid="ei1" eventID="e1" signalID="s1" /><SIGNAL sid="s1">within</SIGNAL><TIMEX3 tid="t1" type="DURATION">five business days</TIMEX3><TLINK eventInstanceID="ei1" relatedToTime="t1” relType="IS_INCLUDED"/>
Time Expressions in TimeML
<TIMEX3 tid="t1" type="DURATION">five business days</TIMEX3>
Dates, times, durations
functionInDocument: Creation_Time, ... (Anchors deictic expressions like “now”, “next Tuesday”)
Follows ISO 8601 time standard
Events in TimeML
<EVENT eid="e1" class="OCCURRENCE" tense=”NONE" aspect="NONE">Delivery</EVENT>
Class: Occurrence: delivery State: on order Reporting: announce I-Action: attempt, offer I-State: believe, want Aspectual: begin, continue Perception: see, watch
Tense: Past, Present, Future, None
Aspect: Progressive, Perfective, Perfective_Progressive, None
Links in TimeML
<TLINK eventInstanceID="ei1" relatedToTime="t1” relType="IS_INCLUDED"/>
TLINK: interval relations
SLINK: Modal: could Factive: forgot Counterfactive: prevent Evidential: said, saw Negative evidential: denied Negative: not
ALINK: Initiation: started to read Culmination: finished reading Termination: stopped reading Continuation: kept reading
TLINK Relations
IdenticalSimultaneousBeforeAfterImmediately beforeImmediately afterIncluding
Is IncludedOverlapsHoldingBeginningBegun byEnding Ended by
<TLINK eventInstanceID="ei1" relatedToTime="t1” relType="IS_INCLUDED"/>
TimeML: Annotation Scheme:An Example
The top commander of a Cambodian resistance force said Thursdayhe has sent a team to recover the remains of a British mine removalexpert kidnapped and presumed killed by Khmer Rouge guerrillastwo years ago.
resist
command
sent recover
Thursday
said now
remove kidnap
2 years
presumed
killedremain
Example
“next Tuesday”:
Tuesday(first(futurep(cal-week,u)))
“five business days”:
nth(futurep(business-day,u),5)delivery
5 business daysorder
next Tuesday
?
Summary of DAML-Time/TimeML
TimeML annotation of text
Algorithms for automatic TimeML annotation of text
Interpret annotations in DAML-Time
Reason in DAML-Time to match requests with services
DAML-Space:A Effort towards an
Ontology of Space
with contributions from Rusty Bobrow, Murray Burke, Dan Connolly, Dejing Dou,
George Ferguson, Andrew Gordon, Pete Haglich, Pat Hayes, Adam Pease, Steve Reed, Richard Waldinger and others
Context
The Semantic Web requires common ontologies with wide acceptance and use.
DAML-S: an ontology of services Development began February 2001 About a dozen people in inner circle Some people have explored using it Institutional status at W3C Version 0.9 just released
DAML-Time: a temporal ontology Development began February 2002 Most work by 3 people Abstract theory 90% complete Mapping between DAML-Time and TimeML Several sites “about to” use it
Want to build on this experience for a spatial ontology.
Aims
A widely available ontology of geographical and other spatial properties and relations
Provide convenient markup and query capabilities for spatial information in Web resources
Adequate abstract coverage of most spatial applications (not necessarily efficient)
Link with special purpose reasoning engines for spatial theories and large-scale GIS databases
Link with various ontological resources (e.g., OpenCyc, SUMO, ...) and annotation schemes
Link with various standards for geographical information (OpenGIS, GML, ...)
Structure of Effort
Abstract Theoryof Space
(FOL)
Complete or Partial Realization in DAML / OWL /
RuleML / ...
SUMO OpenCyc
Cohn Hayes & Chaudhri
Annotation Standards
etc
Existing Standards NLP ExtractionTechniques
Some Principles
Delimiting the effort: Not a theory of physical objects, properties of materials, qualitative physics Link with numerical computation, don’t axiomatize it Link with large geographical DBs, don’t duplicate them
Navigate past controversial issues by Keeping silent on issue Provide easily exercised options
Use textbook logic for abstract theory; DAML/OWL-ize predicate and function declarations
Provide simple, useful entry subontologies
Topics
SPACE TIME
Topology Topology
Dimension --
Orientation & Shape --
Length, area, volume Duration
Lat/long, elevation Clock & calendar
Geopolitical subdivisions --
Granularity Granularity
Aggregates, distributions Temporal aggregates
Topology
Points, arcs, regions, volumesClosed loops and surfacesOrdering relations & “between” in arcs; directions on lines and loopsConnectedness, continuityBoundaries & surfaces, interior & exterior, directed boundaries; “airspace above”Disjoint, touching, bordering, overlapping, containing regions (RCC8); location atHolesNOT open and closed setsNOT pathological topologies
Dimension and Orientation
Abstract characterization of dimension, projections on component dimensionsLinks w topological notions of dimensionFrames of reference: earth-based, person-based, vehicle-based, force-basedRelative orientations: parallel, perpendicularCartesian vs polar coordinate systems, bearing & rangeTransformations between coordinate systemsDegrees of freedomQualitative trigonometry: granularities on orientations2 1/2 dimensions: elevation as 2nd class dimension, system mostly thought of as planarElevation from sea level vs ground levelPlanar vs spherical geometry
Shape
2D vs 3D shapesLinking w shape descriptions in geographical databasesShape descriptors: round, tall, narrow, convex,...Relative shapes: rounder, sharper, ...Same shape as, negative-shape, fits-inSymmetryLinks w functionality of shape In artifacts, shape is almost always functional In natural objects, shape often has consequences? Texture
Size
Length, distance, area, and volumePrecise measuresAlternate descriptions of sizeEnglish-metric conversionsCoarse granularities: order of magnitude, half order of magnitude, implied precision, qualitative measures (large, medium, small) relative to comparison setEncoding uncertainty: bounded error, egg yolk theoriesUncertainty of location vs imprecise regions
Granularity
A city can be viewed as a point, a region, or a volume.How should these different perspectives be accommodated?
One approach: City is an entity with 3D, 2D, and 0D realizations.User can pick which one(s) to use.
Build granularity considerations into spatial ontology from the beginning, not as an add-on.
Spatial Aggregates
What are the most common ways of describing spatial aggregates?
A qualitative theory of distributions.
? Texture
Geologic/Geopolitical Regions
Latitude and Longitude
Natural geographical regions: Land masses: continent, island, ... Bodies of water: ocean, lake, river, ... Terrain features: mountain, valley, forest, desert, ...
Political regions: Countries Political subdivisions: state, province, county, ... Municipalities: city, town, village, ... Residences and street addresses Other: Indian reservations, regulatory zones, ...
Linkages
Exploit the large amount of research on spatial representation and reasoningOpenCyc, SUMO, Cohn, Galton, Hayes & Chaudhri, Hayes, Asher & Vieu, Egenhofer, ForbusAxiomatize best of this work in coherent fashion
Link with existing large ontologies and annotation schemes SUMO, OpenCyc
Ontology should bottom out in existing standards OpenGIS, GML
Target Applications
As drivers for what has to be represented
Flight map system, COA planning, trafficabilityTravel system involving lat/longs, political divisions, weatherAlexandrian Digital Library Geologic and space (NASA) applications (3-D)Cell biology Image interpretation and descriptionRoboticsVirtual reality
For some of these, we are collecting brief descriptions of the requirements for spatial representation and reasoning
Organization
daml-spatial mailing list
Web page - George Ferguson
Coherent construction of abstract theories by small group of people
Committee of interested persons in U.S. and Europe Email for commentary / feedback Telecons every 2 weeks to track issues/progress
Presentations and discussion sessions at relevant workshops
Early realizations of relevant parts of ontology in DAML
Early construction of application-oriented entry subontologies
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