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:
Entretanto, en el condado de Broward, al norte de Miami, tras el escrutinio manual de 428 de los 609 recintos electorales, Gore había ganado 108 nuevos votos.
Postion	Tokenization
1	Entretanto
2	,
3	en
4	el
5	condado
6	de
7	Broward
8	,
9	al
10	norte
11	de
12	Miami
13	,
14	tras
15	el
16	escrutinio
17	manual
18	de
19	428
20	de
21	los
22	609
23	recintos
24	electorales
25	,
26	Gore
27	había
28	ganado
29	108
30	nuevos
31	votos
32	.
Position	Tokenization	UPOS	Head	Deprel
1	Entretanto	ADV	28	advmod
2	,	PUNCT	1	punct
3	en	ADP	5	case
4	el	DET	5	det
5	condado	NOUN	28	obl
6	de	ADP	7	case
7	Broward	PROPN	5	nmod
8	,	PUNCT	10	punct
9	al	ADP	10	case
10	norte	NOUN	5	nmod
11	de	ADP	12	case
12	Miami	PROPN	10	nmod
13	,	PUNCT	5	punct
14	tras	ADP	16	case
15	el	DET	16	det
16	escrutinio	NOUN	28	obl
17	manual	ADJ	16	amod
18	de	ADP	19	case
19	428	NUM	16	nummod
20	de	ADP	23	case
21	los	DET	22	det
22	609	NUM	23	nummod
23	recintos	NOUN	19	nmod
24	electorales	ADJ	23	amod
25	,	PUNCT	16	punct
26	Gore	PROPN	28	nsubj
27	había	AUX	28	aux
28	ganado	VERB	0	root
29	108	NUM	31	nummod
30	nuevos	ADJ	31	amod
31	votos	NOUN	28	obj
32	.	PUNCT	28	punct