The Descent of Hierarchy, and Selection

in RelationalSemantics*

Barbara Rosario, Marti Hearst, Charles Fillmore

UC Berkeley

*with apologies to Charles Darwin

Noun Compounds (NCs)

Technical text is rich with NCs Open-labeled long-term study of the subcutaneous sumatriptan efficacy and tolerability in acute migraine treatment.

Any sequence of nouns that itself functions as a noun asthma hospitalizations health care personnel hand wash

NCs: 3 computational tasks

Identification Syntactic analysis (attachments)

[Baseline [headache frequency]] [[Tension headache] patient]

Our Goal: Semantic analysis Headache treatment treatment for

headache Corticosteroid treatment treatment that uses

corticosteroid

Descent of Hierarchy

Idea: Use the top levels of a lexical

hierarchy to identify semantic relations

Hypothesis: A particular semantic relation holds

between all 2-word NCs that can be categorized by a lexical category pair.

Outline

Related work Linguistic motivation Lexical Hierarchy: MeSH Labeling NC relations

Method and results Discussion of ambiguity

Related work (Semantic analysis of NCs)

Rule-based Finin (1980)

Detailed AI analysis, hand-coded Vanderwende (1994)

automatically extracts semantic information from an on-line dictionary, manipulates a set of handwritten rules. 13 classes, 52% accuracy

Probabilistic Lauer (1995):

probabilistic model, 8 classes, 47% accuracy Lapata (2000)

classifies nominalizations into subject/object. 2 classes, 80% accuracy

Related work (Semantic analysis of NCs)

Lexical Hierarchy Barrett et al. (2001)

WordNet, heuristics to classify a NC given the similarity to a known NC

Rosario and Hearst (2001) MeSH, Neural Network. 18 classes, 60% accuracy

Relations pre-defined

Linguistic Motivation Semantics of the NCs: head-modifier

relationship Head noun has argument structure

Meaning of the head noun determines what kinds of things can be done to it, what it is made of, what it is a part of…

Linguistic Motivation (cont.)

Material + Cutlery Made of steel knife, plastic fork, wooden spoon  

Food + Cutlery Used on meat knife, dessert spoon, salad fork 

Profession + Cutlery Used by chef's knife, butcher's knife

Outline

Related work Linguistic motivation Lexical Hierarchy: MeSH Labeling NC relations

Method and results Discussion of ambiguity

The lexical Hierarchy: MeSH

Tree Structures

1. Anatomy [A] 2. Organisms [B] 3. Diseases [C] 4. Chemicals and Drugs [D] 5. Analytical, Diagnostic and Therapeutic Techniques and Equipment [E] 6. Psychiatry and Psychology [F] 7. Biological Sciences [G] 8. Physical Sciences [H] 9. Anthropology, Education, Sociology and Social Phenomena [I] 10. Technology and Food and Beverages [J] 11. Humanities [K] 12. Information Science [L] 13. Persons [M] 14. Health Care [N] 15. Geographic Locations [Z]

The lexical Hierarchy: MeSH

1. Anatomy [A] Body Regions [A01] 2. [B] Musculoskeletal System [A02] 3. [C] Digestive System [A03] 4. [D] Respiratory System [A04] 5. [E] Urogenital System [A05] 6. [F] …… 7. [G] 8. Physical Sciences [H] 9. [I] 10. [J] 11. [K] 12. [L] 13. [M]

Descending the Hierarchy 1. Anatomy [A] Body Regions [A01] Abdomen

[A01.047] 2. [B] Musculoskeletal System [A02] Back [A01.176] 3. [C] Digestive System [A03] Breast [A01.236] 4. [D] Respiratory System [A04] Extremities

[A01.378] 5. [E] Urogenital System [A05] Head [A01.456] 6. [F] …… Neck [A01.598] 7. [G] …. 8. Physical Sciences [H] 9. [I] 10. [J] 11. [K] 12. [L] 13. [M]

Descending the Hierarchy 1. Anatomy [A] Body Regions [A01] Abdomen

[A01.047] 2. [B] Musculoskeletal System [A02] Back [A01.176] 3. [C] Digestive System [A03] Breast [A01.236] 4. [D] Respiratory System [A04] Extremities

[A01.378] 5. [E] Urogenital System [A05] Head [A01.456] 6. [F] …… Neck [A01.598] 7. [G] …. 8. Physical Sciences [H] Electronics 9. [I] Astronomy 10. [J] Nature 11. [K] Time 12. [L] Weights and Measures 13. [M] ….

Descending the Hierarchy 1. Anatomy [A] Body Regions [A01] Abdomen

[A01.047] 2. [B] Musculoskeletal System [A02] Back [A01.176] 3. [C] Digestive System [A03] Breast [A01.236] 4. [D] Respiratory System [A04] Extremities

[A01.378] 5. [E] Urogenital System [A05] Head [A01.456] 6. [F] …… Neck [A01.598] 7. [G] …. 8. Physical Sciences [H] Electronics Amplifiers 9. [I] Astronomy Electronics, Medical 10. [J] Nature Transducers 11. [K] Time 12. [L] Weights and Measures 13. [M] ….

Descending the Hierarchy 1. Anatomy [A] Body Regions [A01] Abdomen [A01.047] 2. [B] Musculoskeletal System [A02] Back [A01.176] 3. [C] Digestive System [A03] Breast [A01.236] 4. [D] Respiratory System [A04] Extremities [A01.378] 5. [E] Urogenital System [A05] Head [A01.456] 6. [F] …… Neck [A01.598] 7. [G] …. 8. Physical Sciences [H] Electronics Amplifiers 9. [I] Astronomy Electronics, Medical 10. [J] Nature Transducers 11. [K] Time 12. [L] Weights and Measures Calibration 13. [M] …. Metric System Reference Standard

Descending the Hierarchy 1. Anatomy [A] Body Regions [A01] Abdomen [A01.047] 2. [B] Musculoskeletal System [A02] Back [A01.176] 3. [C] Digestive System [A03] Breast [A01.236] 4. [D] Respiratory System [A04] Extremities [A01.378] 5. [E] Urogenital System [A05] Head [A01.456] 6. [F] …… Neck [A01.598] 7. [G] …. 8. Physical Sciences [H] Electronics Amplifiers 9. [I] Astronomy Electronics, Medical 10. [J] Nature Transducers 11. [K] Time 12. [L] Weights and Measures Calibration 13. [M] …. Metric System Reference Standard

Homogeneous

Heterogeneous

Mapping Nouns to MeSH Concepts

headache recurrence C23.888.592.612.441 C23.550.291.937

headache painC23.888.592.612.441 G11.561.796.444

breast cancer cellsA01.236 C04 A11

Levels of Description

headache pain

Level 0: C.23 G.11 Level 1: C23.888 G11.561 Level 1: C23.888.592 G11.561.796 … Original: C23.888.592.612.441 G11.561.796.444

Outline

Related work Linguistic motivation Lexical Hierarchy: MeSH Labeling NC relations

Method and results Discussion of ambiguity

Descent of Hierarchy

Idea: Words falling in homogeneous MeSH

subhierarchies behave “similarly” with respect to relation assignment

Hypothesis: A particular semantic relation holds

between all 2-word NCs that can be categorized by a MeSH category pairs

Grouping the NCs CP: A02 C04 (Musculoskeletal System,

Neoplasms) skull tumors, bone cysts, bone metastases, skull

osteosarcoma… CP: C04 M01 (Neoplasms, Person)

leukemia survivor, lymphoma patients, cancer physician, cancer nurses…

Distribution of Category Pairs

Collection ~70,000 NCs extracted from titles and

abstracts of Medline 2,627 CPs at level 0 (with at least 10 unique

NCs) We analyzed

250 CPs with Anatomy (A) 21 CPs with Natural Science (H01) 3 CPs with Neoplasm (C04)

This represents 10% of total CPs and 20% of total NCs

For each CP

Divide its NCs into “training-testing” sets

“Training”: inspect NCs by hand Start from level 0 0 While NCs are not all similar

descend one level of the hierarchy Repeat until all NCs for that CP are similar

Classification Method

Using the CPs for classification

CP: A02 C04 (Musculoskeletal System, Neoplasms) skull tumors, bone cysts, bone metastases, skull

osteosarcoma

Using the CPs for classification

CP: A02 C04 (Musculoskeletal System, Neoplasms) skull tumors, bone cysts, bone metastases, skull

osteosarcoma Similar NCs All NCs under the CP A02 C04 have the same

semantic relationship Location of disease? Disease in Anatomy?

Using the CPs for classification

CP: A02 C04 (Musculoskeletal System, Neoplasms) skull tumors, bone cysts, bone metastases, skull

osteosarcoma Similar NCs All NCs under the CP A02 C04 have the same

semantic relationship Location of disease? Disease in Anatomy?

Add CP: A02 C04 to the list of classification decisions

Classification decisionsA02 C04

Using the CPs for classification

CP: B06 B06 (Plants, Plants) eucalyptus trees, apple fruits, rice grains, potato plants

Classification decisionsA02 C04

Using the CPs for classification

CP: B06 B06 (Plants, Plants) eucalyptus trees, apple fruits, rice grains, potato plants Similar Same relationship Add CP B06 B06

Classification decisionsA02 C04B06 B06

Using the CPs for classification

CP: C04 M01 (Neoplasms, Person) leukemia survivor, lymphoma patients,

cancer physician, cancer nurses… Person afflicted by Disease? Person who treat

Disease? Too different! Second noun needs to be more specific: Descend

one level for the second noun PersonClassification decisionsA02 C04B06 B06

Using the CPs for classification

CP: C04 M01 (Neoplasm, Person) leukemia survivor, lymphoma patients, cancer

physician, cancer nurses… Too different!

CP: C04 M01.643 (Neoplasms, Patients) leukemia survivor, lymphoma patients Person afflicted by Disease

CP: C04 M01.526 (Neoplasms, Occupational Groups) cancer physician, cancer nurses… Person who treat Disease

OK

Classification decisionsA02 C04B06 B06C04 M01 C04 M01.643 C04 M01.526

Classification Decisions A02 C04 B06 B06 C04 M01

C04 M01.643 C04 M01.526

A01 H01 A01 H01.770 A01 H01.671

A01 H01.671.538 A01 H01.671.868

A01 M01 A01 M01.643 A01 M01.526 A01 M01.898

Classification Decisions + Relations (future work)

A02 C04 Location of Disease B06 B06 Kind of Plants C04 M01

C04 M01.643 Person afflicted by Disease C04 M01.526 Person who treats Disease

A01 H01 A01 H01.770 A01 H01.671

A01 H01.671.538 A01 H01.671.868

A01 M01 A01 M01.643 A01 M01.526 A01 M01.898

Classification Decisions + Relations (future work)

A02 C04 Location of Disease B06 B06 Kind of Plants C04 M01

C04 M01.643 Person afflicted by Disease C04 M01.526 Person who treats Disease

A01 H01 A01 H01.770 A01 H01.671

A01 H01.671.538 A01 H01.671.868

A01 M01 A01 M01.643 Person afflicted by Disease A01 M01.526 A01 M01.898

Classification Decision Levels

Anatomy: 250 CPs 187 (75%) remain first level 56 (22%) descend one level 7 (3%) descend two levels

Natural Science (H01): 21 CPs 1 (4%) remain first level 8 (39%) descend one level 12 (57%) descend two levels

Neoplasms (C04) 3 CPs: 3 (100%) descend one level

Evaluation Test the decisions on “testing” set Count how many NCs that fall in the groups

defined in the classification decisions are similar to each other

Accuracy: Anatomy: 91% accurate Natural Science: 79% Neoplasm: 100%

Total Accuracy : 90.8% Generalization: our 415 classification

decisions cover ~ 46,000 possible CP pairs

Outline

Related work Linguistic motivation Lexical Hierarchy: MeSH Labeling NC relations

Method and results Discussion of ambiguity

Ambiguity – Two Types

Lexical ambiguity: mortality

state of being mortal death rate

Relationship ambiguity: bacteria mortality

death of bacteria death caused by bacteria

Lexical Ambiguity vs. Multiple MeSH Senses

Lexical ambiguity different from multiple MeSH senses Ex: Mortality has 4 senses

Public Health (G) Data Collection Vital Statistics   Mortality Investigative Techniques (E) Data Collection Vital Statistics  

Mortality Information Science (L) Data Collection Vital Statistics   Mortality Population Characteristics (N) Demography Vital Statistics  

Mortality

On average, there are 1.5 MeSH senses per word for the nouns in our collection

Four CasesSingle MeSH senses Multiple MeSH senses

Only one possible relationship: abdomen radiography, aciclovir treatment

Multiple relationships: hospital databases, education efforts, kidney metabolism

Only one possible relationship: alcoholism treatment

Ambiguity of relationship

Multiple relationships bacteria mortality

Four CasesSingle MeSH senses Multiple MeSH senses

Only one possible relationship: abdomen radiography, aciclovir treatment

Multiple relationships: hospital databases, education efforts, kidney metabolism

Only one possible relationship: alcoholism treatment

Ambiguity of relationship

Multiple relationships bacteria mortality

Most problematic cases

… but rare!

Conclusions

Very simple method for assigning semantic relations to two-word technical NCs 90.8% accuracy

Grouping the NCs with respect to their semantic descriptors

Lexical resource (MeSH) useful for this task Use the upper levels of the lexical hierarchy

for an accurate classification, reducing therefore the space of the problem

Future work

Analyze full spectrum of hierarchy NCs with > 2 terms

[[growth hormone] deficiency] Other syntactic structures Non-biomedical words

Other ontologies (e.g.,WordNet)?

And given enough data…

skull character jaw depression nose resuscitation cadaver motion

Thanks!

For more information:http://bailando.sims.berkeley.edu/lin

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