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:
took a bit of searching to discover that POP is probably PoP - plaster of Paris and yes plaster of Paris will slow way down if it is not exposed to air - in fact, if you are building up plaster ("the way you would icing") to do sculpting, which is rather uncommon, you keep the set plaster damp in order to add more unset plaster or you have to wet the area where you will be adding plaster "mud"
Postion	Tokenization
1	took
2	a
3	bit
4	of
5	searching
6	to
7	discover
8	that
9	POP
10	is
11	probably
12	PoP
13	-
14	plaster
15	of
16	Paris
17	and
18	yes
19	plaster
20	of
21	Paris
22	will
23	slow
24	way
25	down
26	if
27	it
28	is
29	not
30	exposed
31	to
32	air
33	-
34	in
35	fact
36	,
37	if
38	you
39	are
40	building
41	up
42	plaster
43	(
44	"
45	the
46	way
47	you
48	would
49	icing
50	"
51	)
52	to
53	do
54	sculpting
55	,
56	which
57	is
58	rather
59	uncommon
60	,
61	you
62	keep
63	the
64	set
65	plaster
66	damp
67	in
68	order
69	to
70	add
71	more
72	unset
73	plaster
74	or
75	you
76	have
77	to
78	wet
79	the
80	area
81	where
82	you
83	will
84	be
85	adding
86	plaster
87	"
88	mud
89	"
Position	Tokenization	UPOS	Head	Deprel
1	took	VERB	0	root
2	a	DET	3	det
3	bit	NOUN	1	obj
4	of	ADP	5	case
5	searching	NOUN	3	nmod
6	to	PART	7	mark
7	discover	VERB	1	csubj
8	that	SCONJ	12	mark
9	POP	NOUN	12	nsubj
10	is	AUX	12	cop
11	probably	ADV	12	advmod
12	PoP	NOUN	7	ccomp
13	-	PUNCT	12	punct
14	plaster	NOUN	12	appos
15	of	ADP	16	case
16	Paris	PROPN	14	nmod
17	and	CCONJ	23	cc
18	yes	INTJ	23	discourse
19	plaster	NOUN	23	nsubj
20	of	ADP	21	case
21	Paris	PROPN	19	nmod
22	will	AUX	23	aux
23	slow	VERB	1	conj
24	way	ADV	25	advmod
25	down	ADV	23	advmod
26	if	SCONJ	30	mark
27	it	PRON	30	nsubj:pass
28	is	AUX	30	aux:pass
29	not	PART	30	advmod
30	exposed	VERB	23	advcl
31	to	ADP	32	case
32	air	NOUN	30	obl
33	-	PUNCT	1	punct
34	in	ADP	35	case
35	fact	NOUN	62	obl
36	,	PUNCT	62	punct
37	if	SCONJ	40	mark
38	you	PRON	40	nsubj
39	are	AUX	40	aux
40	building	VERB	62	advcl
41	up	ADP	40	compound:prt
42	plaster	NOUN	40	obj
43	(	PUNCT	46	punct
44	"	PUNCT	46	punct
45	the	DET	46	det
46	way	NOUN	40	obl
47	you	PRON	49	nsubj
48	would	AUX	49	aux
49	icing	NOUN	46	acl:relcl
50	"	PUNCT	46	punct
51	)	PUNCT	46	punct
52	to	PART	53	mark
53	do	VERB	40	advcl
54	sculpting	NOUN	53	obj
55	,	PUNCT	53	punct
56	which	PRON	59	nsubj
57	is	AUX	59	cop
58	rather	ADV	59	advmod
59	uncommon	ADJ	53	parataxis
60	,	PUNCT	62	punct
61	you	PRON	62	nsubj
62	keep	VERB	1	parataxis
63	the	DET	65	det
64	set	ADJ	65	amod
65	plaster	NOUN	62	obj
66	damp	ADJ	62	xcomp
67	in	ADP	70	mark
68	order	NOUN	67	fixed
69	to	PART	70	mark
70	add	VERB	62	advcl
71	more	ADJ	73	amod
72	unset	ADJ	73	amod
73	plaster	NOUN	70	obj
74	or	CCONJ	76	cc
75	you	PRON	76	nsubj
76	have	VERB	62	conj
77	to	PART	78	mark
78	wet	VERB	76	xcomp
79	the	DET	80	det
80	area	NOUN	78	obj
81	where	SCONJ	85	mark
82	you	PRON	85	nsubj
83	will	AUX	85	aux
84	be	AUX	85	aux
85	adding	VERB	80	acl:relcl
86	plaster	NOUN	88	compound
87	"	PUNCT	88	punct
88	mud	NOUN	85	obj
89	"	PUNCT	88	punct