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:
Los incrementos que más han afectado a los consumidores son los del azúcar, arroz y aceite, mientras que los detergentes, por ejemplo, han duplicado sus precios, al igual que algunas medicinas.
Postion	Tokenization
1	Los
2	incrementos
3	que
4	más
5	han
6	afectado
7	a
8	los
9	consumidores
10	son
11	los
12	del
13	azúcar
14	,
15	arroz
16	y
17	aceite
18	,
19	mientras
20	que
21	los
22	detergentes
23	,
24	por
25	ejemplo
26	,
27	han
28	duplicado
29	sus
30	precios
31	,
32	al
33	igual
34	que
35	algunas
36	medicinas
37	.
Position	Tokenization	UPOS	Head	Deprel
1	Los	DET	2	det
2	incrementos	NOUN	11	nsubj
3	que	PRON	6	nsubj
4	más	ADV	6	advmod
5	han	AUX	6	aux
6	afectado	VERB	2	acl
7	a	ADP	9	case
8	los	DET	9	det
9	consumidores	NOUN	6	obj
10	son	AUX	11	cop
11	los	DET	0	root
12	del	ADP	13	case
13	azúcar	NOUN	11	nmod
14	,	PUNCT	15	punct
15	arroz	NOUN	13	conj
16	y	CCONJ	17	cc
17	aceite	NOUN	13	conj
18	,	PUNCT	28	punct
19	mientras	CCONJ	28	cc
20	que	SCONJ	19	fixed
21	los	DET	22	det
22	detergentes	NOUN	28	nsubj
23	,	PUNCT	24	punct
24	por	ADP	28	advmod
25	ejemplo	NOUN	24	fixed
26	,	PUNCT	24	punct
27	han	AUX	28	aux
28	duplicado	VERB	11	conj
29	sus	DET	30	det
30	precios	NOUN	28	obj
31	,	PUNCT	36	punct
32	al	ADP	36	mark
33	igual	ADJ	32	fixed
34	que	SCONJ	32	fixed
35	algunas	DET	36	det
36	medicinas	NOUN	22	conj
37	.	PUNCT	11	punct