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 pívot fue el máximo encestador de su equipo al lograr 27 puntos y fue bien secundado por el guardia Kobe Bryant, que sumó 22 para los Lakers, mientras que el alero Horace Grant colaboró con 19.
Postion	Tokenization
1	El
2	pívot
3	fue
4	el
5	máximo
6	encestador
7	de
8	su
9	equipo
10	al
11	lograr
12	27
13	puntos
14	y
15	fue
16	bien
17	secundado
18	por
19	el
20	guardia
21	Kobe
22	Bryant
23	,
24	que
25	sumó
26	22
27	para
28	los
29	Lakers
30	,
31	mientras
32	que
33	el
34	alero
35	Horace
36	Grant
37	colaboró
38	con
39	19
40	.
Position	Tokenization	UPOS	Head	Deprel
1	El	DET	2	det
2	pívot	NOUN	6	nsubj
3	fue	AUX	6	cop
4	el	DET	6	det
5	máximo	ADJ	6	amod
6	encestador	NOUN	0	root
7	de	ADP	9	case
8	su	DET	9	det
9	equipo	NOUN	6	nmod
10	al	ADP	11	mark
11	lograr	VERB	6	advcl
12	27	NUM	13	nummod
13	puntos	NOUN	11	obj
14	y	CCONJ	31	cc
15	fue	AUX	17	aux
16	bien	ADV	17	advmod
17	secundado	VERB	31	parataxis
18	por	ADP	20	case
19	el	DET	20	det
20	guardia	NOUN	17	obj
21	Kobe	PROPN	20	appos
22	Bryant	PROPN	21	flat
23	,	PUNCT	25	punct
24	que	PRON	25	nsubj
25	sumó	VERB	20	acl
26	22	NUM	25	obj
27	para	ADP	29	case
28	los	DET	29	det
29	Lakers	PROPN	25	obl
30	,	PUNCT	31	punct
31	mientras	CCONJ	6	conj
32	que	SCONJ	31	fixed
33	el	DET	34	det
34	alero	NOUN	37	nsubj
35	Horace	PROPN	34	appos
36	Grant	PROPN	35	flat
37	colaboró	VERB	31	parataxis
38	con	ADP	39	case
39	19	NUM	37	obj
40	.	PUNCT	6	punct