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:
El senador por Massachusetts consiguió que los más de 4.300 delegados asistentes corearan sin descanso la frase "lucha por Al Gore, porque él está luchando por ti".
Postion	Tokenization
1	El
2	senador
3	por
4	Massachusetts
5	consiguió
6	que
7	los
8	más
9	de
10	4.300
11	delegados
12	asistentes
13	corearan
14	sin
15	descanso
16	la
17	frase
18	"
19	lucha
20	por
21	Al
22	Gore
23	,
24	porque
25	él
26	está
27	luchando
28	por
29	ti
30	"
31	.
Position	Tokenization	UPOS	Head	Deprel
1	El	DET	2	det
2	senador	NOUN	5	nsubj
3	por	ADP	4	case
4	Massachusetts	PROPN	2	nmod
5	consiguió	VERB	0	root
6	que	SCONJ	13	mark
7	los	DET	10	det
8	más	ADV	10	advmod
9	de	ADP	10	case
10	4.300	NUM	11	nummod
11	delegados	NOUN	13	nsubj
12	asistentes	ADJ	11	amod
13	corearan	VERB	5	ccomp
14	sin	ADP	15	case
15	descanso	NOUN	13	obl
16	la	DET	17	det
17	frase	NOUN	13	obj
18	"	PUNCT	19	punct
19	lucha	VERB	17	acl
20	por	ADP	22	case
21	Al	ADP	22	case
22	Gore	PROPN	19	obj
23	,	PUNCT	27	punct
24	porque	SCONJ	27	mark
25	él	PRON	27	nsubj
26	está	AUX	27	aux
27	luchando	VERB	19	advcl
28	por	ADP	29	case
29	ti	PRON	27	obj
30	"	PUNCT	19	punct
31	.	PUNCT	5	punct