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 directora de la adaptación cinematográfica de Yerma, la obra teatral de Federico García Lorca, ha elegido los Alcázares de Sevilla por su belleza.
Postion	Tokenization
1	La
2	directora
3	de
4	la
5	adaptación
6	cinematográfica
7	de
8	Yerma
9	,
10	la
11	obra
12	teatral
13	de
14	Federico
15	García
16	Lorca
17	,
18	ha
19	elegido
20	los
21	Alcázares
22	de
23	Sevilla
24	por
25	su
26	belleza
27	.
Position	Tokenization	UPOS	Head	Deprel
1	La	DET	2	det
2	directora	NOUN	19	nsubj
3	de	ADP	5	case
4	la	DET	5	det
5	adaptación	NOUN	2	nmod
6	cinematográfica	ADJ	5	amod
7	de	ADP	8	case
8	Yerma	PROPN	5	nmod
9	,	PUNCT	11	punct
10	la	DET	11	det
11	obra	NOUN	8	appos
12	teatral	ADJ	11	amod
13	de	ADP	14	case
14	Federico	PROPN	11	nmod
15	García	PROPN	14	flat
16	Lorca	PROPN	14	flat
17	,	PUNCT	11	punct
18	ha	AUX	19	aux
19	elegido	VERB	0	root
20	los	DET	21	det
21	Alcázares	PROPN	19	obj
22	de	ADP	23	case
23	Sevilla	PROPN	21	flat
24	por	ADP	26	case
25	su	DET	26	det
26	belleza	NOUN	19	obl
27	.	PUNCT	19	punct