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:
En otros dos municipios que forman parte del área exterior de este "cinturón rojo", Humanes y Valdemoro, también logró hoy la victoria la lista al Congreso de los Diputados encabezada por José María Aznar.
Postion	Tokenization
1	En
2	otros
3	dos
4	municipios
5	que
6	forman
7	parte
8	del
9	área
10	exterior
11	de
12	este
13	"
14	cinturón
15	rojo
16	"
17	,
18	Humanes
19	y
20	Valdemoro
21	,
22	también
23	logró
24	hoy
25	la
26	victoria
27	la
28	lista
29	al
30	Congreso
31	de
32	los
33	Diputados
34	encabezada
35	por
36	José
37	María
38	Aznar
39	.
Position	Tokenization	UPOS	Head	Deprel
1	En	ADP	4	case
2	otros	DET	4	det
3	dos	NUM	2	nummod
4	municipios	NOUN	23	obl
5	que	PRON	6	nsubj
6	forman	VERB	4	acl
7	parte	NOUN	6	compound
8	del	ADP	9	case
9	área	NOUN	6	obj
10	exterior	ADJ	9	amod
11	de	ADP	14	case
12	este	DET	14	det
13	"	PUNCT	14	punct
14	cinturón	NOUN	9	nmod
15	rojo	ADJ	14	amod
16	"	PUNCT	14	punct
17	,	PUNCT	18	punct
18	Humanes	PROPN	4	appos
19	y	CCONJ	20	cc
20	Valdemoro	PROPN	18	conj
21	,	PUNCT	18	punct
22	también	ADV	23	advmod
23	logró	VERB	0	root
24	hoy	ADV	23	advmod
25	la	DET	26	det
26	victoria	NOUN	23	obj
27	la	DET	28	det
28	lista	NOUN	23	nsubj
29	al	ADP	30	case
30	Congreso	PROPN	28	nmod
31	de	ADP	33	case
32	los	DET	33	det
33	Diputados	PROPN	30	flat
34	encabezada	ADJ	28	amod
35	por	ADP	36	case
36	José	PROPN	34	obj
37	María	PROPN	36	flat
38	Aznar	PROPN	36	flat
39	.	PUNCT	23	punct