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:
La parcela cinematográfica tendrá uno de sus puntos fuertes en el Maratón de cine del Sábado, con cintas como Pan y rosas (Ken Loach) y Yiyi (del taiwanés Edward Yang).
Postion	Tokenization
1	La
2	parcela
3	cinematográfica
4	tendrá
5	uno
6	de
7	sus
8	puntos
9	fuertes
10	en
11	el
12	Maratón
13	de
14	cine
15	del
16	Sábado
17	,
18	con
19	cintas
20	como
21	Pan
22	y
23	rosas
24	(
25	Ken
26	Loach
27	)
28	y
29	Yiyi
30	(
31	del
32	taiwanés
33	Edward
34	Yang
35	)
36	.
Position	Tokenization	UPOS	Head	Deprel
1	La	DET	2	det
2	parcela	NOUN	4	nsubj
3	cinematográfica	ADJ	2	amod
4	tendrá	VERB	0	root
5	uno	PRON	4	obj
6	de	ADP	8	case
7	sus	DET	8	det
8	puntos	NOUN	5	nmod
9	fuertes	ADJ	8	amod
10	en	ADP	12	case
11	el	DET	12	det
12	Maratón	PROPN	4	obl
13	de	ADP	14	case
14	cine	NOUN	12	nmod
15	del	ADP	16	case
16	Sábado	NOUN	12	nmod
17	,	PUNCT	19	punct
18	con	ADP	19	case
19	cintas	NOUN	4	obl
20	como	SCONJ	21	mark
21	Pan	PROPN	19	nmod
22	y	CCONJ	23	cc
23	rosas	PROPN	21	conj
24	(	PUNCT	25	punct
25	Ken	PROPN	21	flat
26	Loach	PROPN	25	flat
27	)	PUNCT	25	punct
28	y	CCONJ	29	cc
29	Yiyi	PROPN	21	conj
30	(	PUNCT	32	punct
31	del	ADP	32	case
32	taiwanés	NOUN	29	nmod
33	Edward	PROPN	32	appos
34	Yang	PROPN	33	flat
35	)	PUNCT	32	punct
36	.	PUNCT	4	punct