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:
Por los derrotados, el alero ex olímpico Shareef Abdur-Rahim logró la mayor puntuación para los Grizzlies al anotar 24 puntos; mientras Mike Bibby logró 23 y Othella Harington, 10.
Postion	Tokenization
1	Por
2	los
3	derrotados
4	,
5	el
6	alero
7	ex
8	olímpico
9	Shareef
10	Abdur-Rahim
11	logró
12	la
13	mayor
14	puntuación
15	para
16	los
17	Grizzlies
18	al
19	anotar
20	24
21	puntos
22	;
23	mientras
24	Mike
25	Bibby
26	logró
27	23
28	y
29	Othella
30	Harington
31	,
32	10
33	.
Position	Tokenization	UPOS	Head	Deprel
1	Por	ADP	3	case
2	los	DET	3	det
3	derrotados	ADJ	11	advmod
4	,	PUNCT	3	punct
5	el	DET	6	det
6	alero	NOUN	11	nsubj
7	ex	ADJ	8	amod
8	olímpico	ADJ	6	amod
9	Shareef	PROPN	6	appos
10	Abdur-Rahim	PROPN	9	flat
11	logró	VERB	0	root
12	la	DET	14	det
13	mayor	ADJ	14	amod
14	puntuación	NOUN	11	obj
15	para	ADP	17	case
16	los	DET	17	det
17	Grizzlies	PROPN	11	obl
18	al	ADP	19	mark
19	anotar	VERB	11	advcl
20	24	NUM	21	nummod
21	puntos	NOUN	19	obj
22	;	PUNCT	26	punct
23	mientras	CCONJ	26	cc
24	Mike	PROPN	26	nsubj
25	Bibby	PROPN	24	flat
26	logró	VERB	11	conj
27	23	NUM	26	obj
28	y	CCONJ	29	cc
29	Othella	PROPN	26	conj
30	Harington	PROPN	29	flat
31	,	PUNCT	32	punct
32	10	NUM	29	appos
33	.	PUNCT	11	punct