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:
Bradley, que perdió las primarias frente a Gore, expresó su apoyo público al candidato a la Presidencia, en cuya campaña prometió que "trabajará duro".
Postion	Tokenization
1	Bradley
2	,
3	que
4	perdió
5	las
6	primarias
7	frente
8	a
9	Gore
10	,
11	expresó
12	su
13	apoyo
14	público
15	al
16	candidato
17	a
18	la
19	Presidencia
20	,
21	en
22	cuya
23	campaña
24	prometió
25	que
26	"
27	trabajará
28	duro
29	"
30	.
Position	Tokenization	UPOS	Head	Deprel
1	Bradley	PROPN	11	nsubj
2	,	PUNCT	4	punct
3	que	PRON	4	nsubj
4	perdió	VERB	1	acl
5	las	DET	6	det
6	primarias	ADJ	4	obj
7	frente	NOUN	9	case
8	a	ADP	7	fixed
9	Gore	PROPN	4	obl
10	,	PUNCT	4	punct
11	expresó	VERB	0	root
12	su	DET	13	det
13	apoyo	NOUN	11	obj
14	público	ADJ	13	amod
15	al	ADP	16	case
16	candidato	NOUN	11	obj
17	a	ADP	19	case
18	la	DET	19	det
19	Presidencia	PROPN	16	nmod
20	,	PUNCT	24	punct
21	en	ADP	23	case
22	cuya	PRON	23	nmod
23	campaña	NOUN	24	obl
24	prometió	VERB	16	acl
25	que	SCONJ	27	mark
26	"	PUNCT	27	punct
27	trabajará	VERB	24	ccomp
28	duro	ADJ	27	advmod
29	"	PUNCT	27	punct
30	.	PUNCT	11	punct