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Adapting NLP Tools and Frame-Semantic Resources for the Semantic Analysis of Ritual Descriptions Nikolina Koleva UdS 22. February 2012 Nikolina Koleva (UdS) 22. February 2012 1 / 22 Outline Introduction 1 NLP Tools and Resources for


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Adapting NLP Tools and Frame-Semantic Resources for the Semantic Analysis of Ritual Descriptions Nikolina Koleva

UdS

  • 22. February 2012

Nikolina Koleva (UdS)

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Outline

1

Introduction

2

NLP Tools and Resources for Ritual Descriptions

3

Characteristics of Ritual Domain

4

Semantic Annotation of Ritual Descriptions

5

Detecting Ritual Structure

6

Summary

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Motivation

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Motivation

interdisciplinary subject, a bunch of challenges

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Motivation

interdisciplinary subject, a bunch of challenges Is there underlying structure of rituals?

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Motivation

interdisciplinary subject, a bunch of challenges Is there underlying structure of rituals? Does "ritual grammar" exist?

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Motivation

interdisciplinary subject, a bunch of challenges Is there underlying structure of rituals? Does "ritual grammar" exist? Is it universal?

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Motivation

interdisciplinary subject, a bunch of challenges Is there underlying structure of rituals? Does "ritual grammar" exist? Is it universal? There is evidence for variances and similarities in rituals wrt.

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Motivation

interdisciplinary subject, a bunch of challenges Is there underlying structure of rituals? Does "ritual grammar" exist? Is it universal? There is evidence for variances and similarities in rituals wrt.

◮ culture Nikolina Koleva (UdS)

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Motivation

interdisciplinary subject, a bunch of challenges Is there underlying structure of rituals? Does "ritual grammar" exist? Is it universal? There is evidence for variances and similarities in rituals wrt.

◮ culture ◮ time Nikolina Koleva (UdS)

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The Tasks

detection of complex event sequences

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The Tasks

detection of complex event sequences finding participants, objects, places and times involved in the events

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The Tasks

detection of complex event sequences finding participants, objects, places and times involved in the events How?

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The Tasks

detection of complex event sequences finding participants, objects, places and times involved in the events How? → using NLP tools

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The Tasks

detection of complex event sequences finding participants, objects, places and times involved in the events How? → using NLP tools recognition of variations and regularities of rituals

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The Tasks

detection of complex event sequences finding participants, objects, places and times involved in the events How? → using NLP tools recognition of variations and regularities of rituals focus on discourse semantic aspects due to complex event sequences

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Difficulties

no all-encompassing theoretical framework for ritual analysis thus recurrent structures in event sequences are unknown descriptions of rituals have different text features than texts used for the development of the used NLP tools → Need for adaptation

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Resources and Tools for Analysis of Ritual Structure

Frame Semantics

◮ powerful framework: concept of scenario frames connected by frame

relations and role inheritance

Lexical Ontology, e.g. WordNet, for variation analysis in characteristics of events across rituals Semantically annotated corpora and reference ontology enables reasoning with external knowledge resources

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Main steps

1 corpus creation and annotation ◮ contains descriptions of different cultures ◮ annotated with linguistic and ritual-specific tags 2 analysis of the ritual structure ◮ deployment of logical and statistical methods for the detection of

recurring structures and systematic variances in ritual descriptions based on semantic annotation

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Ritual Descriptions

collected from different sources

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Ritual Descriptions

collected from different sources

◮ Hindu rituals from Nepal Nikolina Koleva (UdS)

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Ritual Descriptions

collected from different sources

◮ Hindu rituals from Nepal ◮ Middle East Nikolina Koleva (UdS)

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Ritual Descriptions

collected from different sources

◮ Hindu rituals from Nepal ◮ Middle East

textual sources

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Ritual Descriptions

collected from different sources

◮ Hindu rituals from Nepal ◮ Middle East

textual sources

◮ theory-oriented studies by ritual researchers that deal with religious,

ethnologic and social rituals (used to build ritual specific ontology)

Nikolina Koleva (UdS)

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Ritual Descriptions

collected from different sources

◮ Hindu rituals from Nepal ◮ Middle East

textual sources

◮ theory-oriented studies by ritual researchers that deal with religious,

ethnologic and social rituals (used to build ritual specific ontology)

◮ descriptions of rituals Nikolina Koleva (UdS)

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Ritual Descriptions

collected from different sources

◮ Hindu rituals from Nepal ◮ Middle East

textual sources

◮ theory-oriented studies by ritual researchers that deal with religious,

ethnologic and social rituals (used to build ritual specific ontology)

◮ descriptions of rituals 1

ethnographic observations (How rituals are performed in modern times?)

Nikolina Koleva (UdS)

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Ritual Descriptions

collected from different sources

◮ Hindu rituals from Nepal ◮ Middle East

textual sources

◮ theory-oriented studies by ritual researchers that deal with religious,

ethnologic and social rituals (used to build ritual specific ontology)

◮ descriptions of rituals 1

ethnographic observations (How rituals are performed in modern times?)

2

ritual manuals (translations of original manuals that prescribe a ritual)

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Ritual Descriptions

collected from different sources

◮ Hindu rituals from Nepal ◮ Middle East

textual sources

◮ theory-oriented studies by ritual researchers that deal with religious,

ethnologic and social rituals (used to build ritual specific ontology)

◮ descriptions of rituals 1

ethnographic observations (How rituals are performed in modern times?)

2

ritual manuals (translations of original manuals that prescribe a ritual)

◮ not trivial alignment of manuals that mention only relevant part of the

events to an exhaustive (possibly subjective description)

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Text Characteristics

foreign terms

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Text Characteristics

foreign terms

◮ He sweeps the place for the sacrificial fire with kuśa. Nikolina Koleva (UdS)

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Text Characteristics

foreign terms

◮ He sweeps the place for the sacrificial fire with kuśa.

→ He sweeps the place for the sacrificial fire with <grass *kuśa>.

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Text Characteristics

foreign terms

◮ He sweeps the place for the sacrificial fire with kuśa.

→ He sweeps the place for the sacrificial fire with <grass *kuśa>.

fixed expressions that often have to be spoken

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Text Characteristics

foreign terms

◮ He sweeps the place for the sacrificial fire with kuśa.

→ He sweeps the place for the sacrificial fire with <grass *kuśa>.

fixed expressions that often have to be spoken

◮ Salutation to Kubera reciting the mantra arddha-mãsãh. Nikolina Koleva (UdS)

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Text Characteristics

foreign terms

◮ He sweeps the place for the sacrificial fire with kuśa.

→ He sweeps the place for the sacrificial fire with <grass *kuśa>.

fixed expressions that often have to be spoken

◮ Salutation to Kubera reciting the mantra arddha-mãsãh.

→replace with placeholders during processing and reinsert them afterwards

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Text Characteristics

foreign terms

◮ He sweeps the place for the sacrificial fire with kuśa.

→ He sweeps the place for the sacrificial fire with <grass *kuśa>.

fixed expressions that often have to be spoken

◮ Salutation to Kubera reciting the mantra arddha-mãsãh.

→replace with placeholders during processing and reinsert them afterwards

Imperatives, PPs and nested sentences

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Text Characteristics

foreign terms

◮ He sweeps the place for the sacrificial fire with kuśa.

→ He sweeps the place for the sacrificial fire with <grass *kuśa>.

fixed expressions that often have to be spoken

◮ Salutation to Kubera reciting the mantra arddha-mãsãh.

→replace with placeholders during processing and reinsert them afterwards

Imperatives, PPs and nested sentences

◮ very common and difficult to process Nikolina Koleva (UdS)

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Text Characteristics

foreign terms

◮ He sweeps the place for the sacrificial fire with kuśa.

→ He sweeps the place for the sacrificial fire with <grass *kuśa>.

fixed expressions that often have to be spoken

◮ Salutation to Kubera reciting the mantra arddha-mãsãh.

→replace with placeholders during processing and reinsert them afterwards

Imperatives, PPs and nested sentences

◮ very common and difficult to process

→ chunks are sufficient for semantic role labeling

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Text Characteristics

foreign terms

◮ He sweeps the place for the sacrificial fire with kuśa.

→ He sweeps the place for the sacrificial fire with <grass *kuśa>.

fixed expressions that often have to be spoken

◮ Salutation to Kubera reciting the mantra arddha-mãsãh.

→replace with placeholders during processing and reinsert them afterwards

Imperatives, PPs and nested sentences

◮ very common and difficult to process

→ chunks are sufficient for semantic role labeling

comments occurence: not each sentence describes the ritual

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Sentence Classification

Salutation to Kubera reciting the mantra arddha-mãsãh.

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Sentence Classification

Salutation to Kubera reciting the mantra arddha-mãsãh.

◮ indicates event happening during the ritual performance: factual Nikolina Koleva (UdS)

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Sentence Classification

Salutation to Kubera reciting the mantra arddha-mãsãh.

◮ indicates event happening during the ritual performance: factual

The involvement of the nephews can be understood as a symbolic action to address those of the following generation who do not belong to lineage of the deceased.

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Sentence Classification

Salutation to Kubera reciting the mantra arddha-mãsãh.

◮ indicates event happening during the ritual performance: factual

The involvement of the nephews can be understood as a symbolic action to address those of the following generation who do not belong to lineage of the deceased.

◮ another level of information, clear interpretation or comment:

interpretative /ignored for the frame annotation/

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Sentence Classification

Salutation to Kubera reciting the mantra arddha-mãsãh.

◮ indicates event happening during the ritual performance: factual

The involvement of the nephews can be understood as a symbolic action to address those of the following generation who do not belong to lineage of the deceased.

◮ another level of information, clear interpretation or comment:

interpretative /ignored for the frame annotation/

The wife of the chief mourner [...] will carry a symbolic mat that represents the bed of the deceased[...].

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Sentence Classification

Salutation to Kubera reciting the mantra arddha-mãsãh.

◮ indicates event happening during the ritual performance: factual

The involvement of the nephews can be understood as a symbolic action to address those of the following generation who do not belong to lineage of the deceased.

◮ another level of information, clear interpretation or comment:

interpretative /ignored for the frame annotation/

The wife of the chief mourner [...] will carry a symbolic mat that represents the bed of the deceased[...].

◮ ambiguous wrt. these classes, or contain both Nikolina Koleva (UdS)

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Linguistic Processing

many special non-English characters: ś, or even tokens: Gen .eśa

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Linguistic Processing

many special non-English characters: ś, or even tokens: Gen .eśa

◮ employ rule-based tokenizer that uses Unicode character ranges Nikolina Koleva (UdS)

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Linguistic Processing

many special non-English characters: ś, or even tokens: Gen .eśa

◮ employ rule-based tokenizer that uses Unicode character ranges

poor results for PoS-Tagging and Chunking

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Linguistic Processing

many special non-English characters: ś, or even tokens: Gen .eśa

◮ employ rule-based tokenizer that uses Unicode character ranges

poor results for PoS-Tagging and Chunking

◮ a lot of unseen tokens Nikolina Koleva (UdS)

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Linguistic Processing

many special non-English characters: ś, or even tokens: Gen .eśa

◮ employ rule-based tokenizer that uses Unicode character ranges

poor results for PoS-Tagging and Chunking

◮ a lot of unseen tokens ◮ many rare uncommon constructions Nikolina Koleva (UdS)

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Linguistic Processing

many special non-English characters: ś, or even tokens: Gen .eśa

◮ employ rule-based tokenizer that uses Unicode character ranges

poor results for PoS-Tagging and Chunking

◮ a lot of unseen tokens ◮ many rare uncommon constructions

→ experiment with different scenarios for the domain adaptation

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Experimental Design for Adaptation

two sources

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Experimental Design for Adaptation

two sources

◮ 532 sentences of ritual descriptions, manually annotated with PoS and

Chunks

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Experimental Design for Adaptation

two sources

◮ 532 sentences of ritual descriptions, manually annotated with PoS and

Chunks

◮ Wall Street Journal corpus Nikolina Koleva (UdS)

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Experimental Design for Adaptation

two sources

◮ 532 sentences of ritual descriptions, manually annotated with PoS and

Chunks

◮ Wall Street Journal corpus

10-fold cross-validation for evaluation

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Evaluation of models for PoS-Tagging

Training data Accuracy (%) WSJ 90.90 RIT 94.82 WSJ + RIT 95.72 WSJ + RIT↑ 96.23 WSJ↓ + RIT 95.25 WSJ × RIT 96.86 WSJ × RIT ↑ 96.85 WSJ ↓ × RIT 95.92

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Evaluation of models for Chunking

Training data F-measure(%) WSJ 86.6 RIT 85.7 WSJ + RIT 86.6 WSJ + RIT↑ 88.1 WSJ↓ + RIT 83.1 WSJ × RIT 74.4 WSJ × RIT ↑ 81.3 WSJ ↓ × RIT 73.3

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Anaphora and Coreference Resolution

  • 1. The father should touch the girl [...]. Let him give a golden

coin as ritual fee[...].

  • 2. Let the girl sit on the seat [...]. Let the girl wash her face [...].

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Anaphora and Coreference Resolution

  • 1. The father should touch the girl [...]. Let him give a golden

coin as ritual fee[...].

  • 2. Let the girl sit on the seat [...]. Let the girl wash her face [...].

BART /machine learning toolkit/; output entire coreference chain JavaRAP /rule-based/; generate only anaphor-antecedent pairs

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Evaluation of Anaphora and Coreference Resolution

26 anaphor-antecedent pairs that correspond to 10 coreference chains

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Evaluation of Anaphora and Coreference Resolution

26 anaphor-antecedent pairs that correspond to 10 coreference chains JavaRAP: 61.5% correct pairs found; evaluation only for anaphora resolution

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Evaluation of Anaphora and Coreference Resolution

26 anaphor-antecedent pairs that correspond to 10 coreference chains JavaRAP: 61.5% correct pairs found; evaluation only for anaphora resolution

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Semantic Annotation of Ritual Descriptions

automatic extraction of verbs

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Semantic Annotation of Ritual Descriptions

automatic extraction of verbs map the ritual actions to frames in FrameNet

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Semantic Annotation of Ritual Descriptions

automatic extraction of verbs map the ritual actions to frames in FrameNet 80% of the verbs from the ritual corpus are contained as lexical units

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Semantic Annotation of Ritual Descriptions

automatic extraction of verbs map the ritual actions to frames in FrameNet 80% of the verbs from the ritual corpus are contained as lexical units

◮ some of them are equivalent only at a lexical level, occur in different

senses

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Semantic Annotation of Ritual Descriptions

automatic extraction of verbs map the ritual actions to frames in FrameNet 80% of the verbs from the ritual corpus are contained as lexical units

◮ some of them are equivalent only at a lexical level, occur in different

senses

frames of FrameNet are too abstract for annotation of ritual descriptions

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Semantic Annotation of Ritual Descriptions

automatic extraction of verbs map the ritual actions to frames in FrameNet 80% of the verbs from the ritual corpus are contained as lexical units

◮ some of them are equivalent only at a lexical level, occur in different

senses

frames of FrameNet are too abstract for annotation of ritual descriptions → new frames have to be designed

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  • 22. February 2012

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Semantic Annotation of Ritual Descriptions

automatic extraction of verbs map the ritual actions to frames in FrameNet 80% of the verbs from the ritual corpus are contained as lexical units

◮ some of them are equivalent only at a lexical level, occur in different

senses

frames of FrameNet are too abstract for annotation of ritual descriptions → new frames have to be designed train a frame-semantic labeler on initial frame inventory and annotated corpus (manually created)

Nikolina Koleva (UdS)

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Semantic Annotation of Ritual Descriptions

automatic extraction of verbs map the ritual actions to frames in FrameNet 80% of the verbs from the ritual corpus are contained as lexical units

◮ some of them are equivalent only at a lexical level, occur in different

senses

frames of FrameNet are too abstract for annotation of ritual descriptions → new frames have to be designed train a frame-semantic labeler on initial frame inventory and annotated corpus (manually created) manual correction after the automatic assignment of semantic roles

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Detecting Ritual Structure |

  • 1. "... the boy sits downChange_posture south of the teacher. (The

teacher) takesTaking flowers, sandal, Areca nut and clothes and declaresText_creation the ritual decision to selectChoosing the Brahmin by sayingText_creation the mantra ..."

  • 2. "... (the teacher) placesPlacing (fire in a vessel of bell metal) in

front of himself. Having takenTaking flowers, sandal, Areca nut, clothing etc. he should selectChoosing a Brahmin. The Brahmin is selected withText_creation" the mantra ..."

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Detecting Ritual Structure ||

interpret each frame and its roles as atomic symbol find global alignment between n sequences describing the same ritual

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Summary

collecting texts: manuals and descriptions analysis of the domain characteristics adaptation of preprocessing tools and semantic resources detection of ritual structure and possible subsequences

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Literature

[1] Nils Reiter, Oliver Hellwig, Anette Frank, Irina Gossmann, Borayin Maitreya Larios, Julio Rodrigues, and Britta Zeller. "Adapting NLP Tools and Frame-Semantic Resources for the Semantic Analysis of Ritual Descriptions". In: C. Sporleder, A. van den Bosch, and K. Zervanou (Eds.), Language Technology for Cultural Heritage. Selected Papers from the LaTeCH Workshop Series, Series: Theory and Applications of Natural Language Processing. Heidelberg: Springer, 2011. [2] Nils Reiter, Oliver Hellwig, Anand Mishra, Anette Frank, Irina Gossmann, Borayin Maitreya Larios, Julio Rodrigues, and Britta Zeller. "Adapting Standard NLP Tools and Resources to the Processing of Ritual Descriptions". Proceedings of ECAI 2010 workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities.

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Thank you for your attention!

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