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:
Representaron dos obras, ambas en un mes de octubre: El burlador de Sevilla, de Tirso de Molina, y El rey Lear, de Shakespeare, con escenografía de Paco Nieva.
Postion	Tokenization
1	Representaron
2	dos
3	obras
4	,
5	ambas
6	en
7	un
8	mes
9	de
10	octubre
11	:
12	El
13	burlador
14	de
15	Sevilla
16	,
17	de
18	Tirso
19	de
20	Molina
21	,
22	y
23	El
24	rey
25	Lear
26	,
27	de
28	Shakespeare
29	,
30	con
31	escenografía
32	de
33	Paco
34	Nieva
35	.
Position	Tokenization	UPOS	Head	Deprel
1	Representaron	VERB	0	root
2	dos	NUM	3	nummod
3	obras	NOUN	1	obj
4	,	PUNCT	5	punct
5	ambas	NUM	3	appos
6	en	ADP	8	case
7	un	DET	8	det
8	mes	NOUN	5	nmod
9	de	ADP	10	case
10	octubre	NOUN	8	nmod
11	:	PUNCT	13	punct
12	El	DET	13	det
13	burlador	PROPN	3	appos
14	de	ADP	15	case
15	Sevilla	PROPN	12	flat
16	,	PUNCT	18	punct
17	de	ADP	18	case
18	Tirso	PROPN	12	nmod
19	de	ADP	20	case
20	Molina	PROPN	18	flat
21	,	PUNCT	18	punct
22	y	CCONJ	24	cc
23	El	DET	24	det
24	rey	PROPN	13	conj
25	Lear	PROPN	24	flat
26	,	PUNCT	28	punct
27	de	ADP	28	case
28	Shakespeare	PROPN	23	nmod
29	,	PUNCT	28	punct
30	con	ADP	31	case
31	escenografía	NOUN	3	nmod
32	de	ADP	33	case
33	Paco	PROPN	31	nmod
34	Nieva	PROPN	33	flat
35	.	PUNCT	1	punct