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:
Igualmente, defendió la candidatura a la Alcaldía por el FPOE de Hilmar Kabas, quien protagonizó una campaña electoral en la capital austriaca para los comicios generales del año pasado que fue muy criticada, debido a sus contenidos xenófobos.
Postion	Tokenization
1	Igualmente
2	,
3	defendió
4	la
5	candidatura
6	a
7	la
8	Alcaldía
9	por
10	el
11	FPOE
12	de
13	Hilmar
14	Kabas
15	,
16	quien
17	protagonizó
18	una
19	campaña
20	electoral
21	en
22	la
23	capital
24	austriaca
25	para
26	los
27	comicios
28	generales
29	del
30	año
31	pasado
32	que
33	fue
34	muy
35	criticada
36	,
37	debido
38	a
39	sus
40	contenidos
41	xenófobos
42	.
Position	Tokenization	UPOS	Head	Deprel
1	Igualmente	ADV	3	advmod
2	,	PUNCT	1	punct
3	defendió	VERB	0	root
4	la	DET	5	det
5	candidatura	NOUN	3	obj
6	a	ADP	8	case
7	la	DET	8	det
8	Alcaldía	PROPN	5	nmod
9	por	ADP	11	case
10	el	DET	11	det
11	FPOE	PROPN	5	nmod
12	de	ADP	13	case
13	Hilmar	PROPN	5	nmod
14	Kabas	PROPN	13	flat
15	,	PUNCT	17	punct
16	quien	PRON	17	nsubj
17	protagonizó	VERB	13	acl
18	una	DET	19	det
19	campaña	NOUN	17	obj
20	electoral	ADJ	19	amod
21	en	ADP	23	case
22	la	DET	23	det
23	capital	NOUN	19	nmod
24	austriaca	ADJ	23	amod
25	para	ADP	27	case
26	los	DET	27	det
27	comicios	NOUN	19	nmod
28	generales	ADJ	27	amod
29	del	ADP	30	case
30	año	NOUN	27	nmod
31	pasado	ADJ	30	amod
32	que	PRON	35	nsubj
33	fue	AUX	35	cop
34	muy	ADV	35	advmod
35	criticada	ADJ	19	acl
36	,	PUNCT	40	punct
37	debido	ADJ	40	case
38	a	ADP	37	fixed
39	sus	DET	40	det
40	contenidos	NOUN	35	obl
41	xenófobos	ADJ	40	amod
42	.	PUNCT	3	punct