As a helpful and smart assistant, your task is to parse a given text in any language to Universal Dependency (UD) format including POS tags and dependency relations (HEAD and DEPREL).
Key Components of UD Annotation:
1. Tokens: The fundamental units within UD are tokens. These can be individual words, punctuation marks, or even parts of multi-word expressions. Each token has several associated attributes.
2. UPOS Tags: The UPOS field in the CoNLL-U format represents the universal part-of-speech tag assigned to each word. This tag is part of a universal POS tag set designed to be applicable across different languages. The UPOS tags include categories such as NOUN, VERB, ADJ (adjective), ADV (adverb), PRON (pronoun), DET (determiner), and more. 
3. Dependency Relations: Dependency relations are the core of the syntactic representation. They form a tree structure over the tokens in a sentence. Here's how they work:
    - HEAD: This field indicates the head of the current word. The head is the word that the current word is connected to in the dependency parse tree. The value is an integer that corresponds to the ID of the head word within the same sentence. A value of zero (0) indicates that the word is the root of the sentence.
    - DEPREL: The DEPREL field specifies the type of dependency relation between the current word and its head (as specified in the HEAD field). The value is a universal dependency relation or a language-specific subtype of such a relation.
Note: Blank lines are used to mark the boundaries between sentences.
Example:
Let's analyze this sentence with its UD annotation:
"The big dog chased the cat."
1. Tokenization:
- The
- big
- dog
- chased
- the
- cat
- .
2. UPOS Tags:
- The: DET
- big: ADJ
- dog: NOUN
- chased: VERB
- the: DET
- cat: NOUN
- .: PUNCT
3. Head node (parent):
- The: the parent of this word is "dog" at position 3
- big: the parent of this word is "dog" at position 3
- dog: the parent of this word is "chased" at position 4
- chased: this is the root node, therefore its head is 0
- the: the parent of this word is "cat" at position 6
- cat: the parent of this word is "chased" at position 4
- .: the parent of this word is "chased" at position 4
3. Dependency Relations:
- root(ROOT, chased)
- det(dog, The)
- amod(dog, big)
- nsubj(chased, dog)
- det(cat, the)
- obj(chased, cat)
Combining the above annotations, the final output in UD format is:
Position	Tokenization	UPOS	Head	Deprel
1	The	DET	3	det
2	big	ADJ	3	amod
3	dog	NOUN	4	nsubj
4	chased	VERB	0	ROOT
5	the	DET	6	det
6	cat	NOUN	4	obj
7	.	PUNCT	4	punct
Generate UD annotations for the following tokenized text:
We also know how Dan Rather libeled George Bush and impugned his service in the Texas Air National Guard on a "60 Minutes II" report based largely on forged documents.
Postion	Tokenization
1	We
2	also
3	know
4	how
5	Dan
6	Rather
7	libeled
8	George
9	Bush
10	and
11	impugned
12	his
13	service
14	in
15	the
16	Texas
17	Air
18	National
19	Guard
20	on
21	a
22	"
23	60
24	Minutes
25	II
26	"
27	report
28	based
29	largely
30	on
31	forged
32	documents
33	.
Position	Tokenization	UPOS	Head	Deprel
1	We	PRON	3	nsubj
2	also	ADV	3	advmod
3	know	VERB	0	root
4	how	SCONJ	7	mark
5	Dan	PROPN	7	nsubj
6	Rather	PROPN	5	flat
7	libeled	VERB	3	ccomp
8	George	PROPN	7	obj
9	Bush	PROPN	8	flat
10	and	CCONJ	11	cc
11	impugned	VERB	7	conj
12	his	PRON	13	nmod:poss
13	service	NOUN	11	obj
14	in	ADP	19	case
15	the	DET	19	det
16	Texas	PROPN	19	compound
17	Air	PROPN	19	compound
18	National	PROPN	19	compound
19	Guard	PROPN	13	nmod
20	on	ADP	27	case
21	a	DET	27	det
22	"	PUNCT	24	punct
23	60	NUM	24	nummod
24	Minutes	PROPN	27	compound
25	II	NUM	24	nummod
26	"	PUNCT	24	punct
27	report	NOUN	11	obl
28	based	VERB	32	case
29	largely	ADV	32	advmod
30	on	ADP	32	case
31	forged	VERB	32	amod
32	documents	NOUN	11	obl
33	.	PUNCT	3	punct