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:
Kayani is well known and liked in Kabul as during the last year he led the Pakistani delegation in the tripartite military meetings with the Afghan and US military on issues related to border issues.
Postion	Tokenization
1	Kayani
2	is
3	well
4	known
5	and
6	liked
7	in
8	Kabul
9	as
10	during
11	the
12	last
13	year
14	he
15	led
16	the
17	Pakistani
18	delegation
19	in
20	the
21	tripartite
22	military
23	meetings
24	with
25	the
26	Afghan
27	and
28	US
29	military
30	on
31	issues
32	related
33	to
34	border
35	issues
36	.
Position	Tokenization	UPOS	Head	Deprel
1	Kayani	PROPN	4	nsubj:pass
2	is	AUX	4	aux:pass
3	well	ADV	4	advmod
4	known	VERB	0	root
5	and	CCONJ	6	cc
6	liked	VERB	4	conj
7	in	ADP	8	case
8	Kabul	PROPN	6	obl
9	as	SCONJ	15	mark
10	during	ADP	13	case
11	the	DET	13	det
12	last	ADJ	13	amod
13	year	NOUN	15	obl
14	he	PRON	15	nsubj
15	led	VERB	6	advcl
16	the	DET	18	det
17	Pakistani	ADJ	18	amod
18	delegation	NOUN	15	obj
19	in	ADP	23	case
20	the	DET	23	det
21	tripartite	ADJ	23	amod
22	military	ADJ	23	amod
23	meetings	NOUN	15	obl
24	with	ADP	29	case
25	the	DET	29	det
26	Afghan	ADJ	29	amod
27	and	CCONJ	28	cc
28	US	PROPN	26	conj
29	military	NOUN	23	nmod
30	on	ADP	31	case
31	issues	NOUN	23	nmod
32	related	ADJ	31	amod
33	to	ADP	35	case
34	border	NOUN	35	compound
35	issues	NOUN	32	obl
36	.	PUNCT	4	punct