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Discussion

Francis: Treebanking is important but only Dan does it

Dan: Montse used to do it too

Francis: … but we need a reminder/walkthrough of how. Also, I need a reminder of a few things. Eg: I know I want the tree that has X type in it, so I go through the trees and I’d like to save some of my steps to repeat them more than once. But let’s start with a walkthrough:

Dan: Ok, what I will show you is how I run though the steps of grammar modification/updating a treebank, inspecting the results and repeating the loop. My procedures has roots in an older machinery with a lisp-based interface, I am still partially using that, but a person in the room doesn’t use that. … I use this $LOGONROOT/parse script, but there are other ways to do this first part. Of course I also need to know which set of profiles I want to use:

[ONSCREEN]

danf@baseque3:~$ $LOGONROOT/parse –terg/ace –protocol 2 –best 1 –count 4 hike

[/ONSCREEN]

I will talk through these arguments:

First argument is which grammar and which engine you want to use. This is in the dot.tsdbrc file. (–terg)

Other arguments are –protocol (which for me) means “store the edge relations”, I want to store the packed forest, what else does that do, woodley, (Woodley: store the forest). Stefan used to suggest –best 0 but that doesn’t make sense for me, I prefer to “unpack 1 tree”. –count 4 is how many cpus I can use. Last argument is profile (hike). So I call that…

[ONSCREEN] LKB loads grammar … [/ONSCREEN]

[Dan talks about how this shows how he still uses LKB under the hood]

Some discussion about how this isn’t really necessary…

Some discussion about how this relates to the loading of malrules…

… so the engine has now parsed this and has stored it in a directory, `erg/trunk/hike/DATE/ace’

So I can now go back to the treebanking tool, answer (or fftb, which answer invokes)

[People complain of the long command on the screen]

Dan: I said I would show people how I do this, not …

Woodley: this thing called answer is a 20 line script written by Oe in order to hide people from the truth … I’ve clarified what I wanted to clarify

Dan: I have copy and paste function and the history program in my shell so I have a way to invoke that long command. I do so, it opens a webbrowser [pointing to 127.0.0.1:50768/private/session?0] …

Francis: We see an exuberant use of color …

Dan: green is great, red is disappointing, I get a lot of browns, which means I have added some ambiguity. The yellow means that I have stuff I haven’t really added. Down here for example, I see a brown. I can say “show me that item” [he clicks on it], and I see that it’s actually spurious…

Glenn: asks a question about this particular example, whether this is a case where the ERG blocks on semantics

Woodley: What is an expletive index

Dan: it’s an ‘it’ or ‘there’,

Woodley: how are those indices? I’m being a bit snarkey, there is not semantic difference because they have no semantics

Francis: —moving on!—

Dan: ok, so I pick the one I wanted …, now I can see the tree that I want by clicking ‘accept’, and I am now taken to the next one which has a difference, here we see an example where I have recently conceded that ‘on’ can be an intransitive prep. Here I have some ambiguity then, as in “Saturday, he went”~“On, he went”. I had to retouch a lot of trees because of this, but there are a few , not in the 17,000 that I had to retouch, where I wanted this new analysis … anyway, life.

Glenn: for the people who don’t do treebanking, this is what they’re scared of

Dan: I knew what I was in for. [Gives another example of something similar where he changed his mind about the copula be and a comma] —:So if we’re still actively developing the grammar, we probably shouldn’t be treebanking.

Dan: No, that’s the wrong thing to learn, I made a conscious decision to do this because I had a spare month, mostly, things aren’t like this. For example, in this ‘hike’ corpus, I didn’t actually have a lot of changes. I think the lesson here is to do treebanking all the time so that when you make a change, you have a small amount of things to change each time.d

Francis: You’ll note that this tool uses your previous work so that as long as you’re continuously treebanking, you’ll just have a little bit of work to do each time you do it.

Luis: Treebanking may force you to deal with amigiuity early on, you waited a long time to deal with this ambiguity, would you have preferred to have done this earlier in the development of this project? (question continues …)

Dan: this particular example was on which was relatively rare, so I waited until I was ready to deal with it.

Luis: If you know you have to deal with it eventually, why don’t you do it earlier

Woodley: It’s not that he has to redo anything

Luis: but that descriminant…

Dan: …didn’t exist before

Luis: fair enough

Francis: so Dan fixed more important problems first…

Luis: I see now, that problem didn’t exist before, now he’s decided to work on it

Glenn: when you were in your blissful period, is there a sense of a generalization which is true now…because you’re … when you’re adding a constraint, …

Dan: the types were all there, I had them, I just added “on” to a new class which was already there

Dan: we probably wasted enough time on this, let me show you something else…Here we see that I can highlight a part of a substring and I can see what options I have for, which rules can span this string. I can select one and it will try to build a tree using that rule for this string, and try to find a spanning parse for the rest. This is a way to force the machine to use a particular rule.

Glenn: where’s the part where you’re certifying your choices?

Dan: I choose “accept” here, it’s hard to see because of my font sizes, but this is where I click.

Dan: here is one more instance, “don’t be tricked by that” is “by” the passive by or the locative by? I know that it’s the passive by in this case, so I can click here and . There is some efficiency stuff which actually creates some false potential analyses here, so you can actually turn it off if your grammar is small enough that you don’t hit resource limits when parsing with it off.

Dan: ok, and now I’m back at the overview, everthing is green or yellow, and I’m ready to exit.

Woodley: the command line that you had people copy, has some –browser=…, what that actually is is a shell script from Oe which does some magic to deal with LD_LIBRARY_PATH

Francis: for example, someone without logon would have a hard time finding these scripts

[ Woodley takes screen to show how to replicate these command without having logon ] Woodley: this is OSX, there is no logon for OSX, the libtsdb you can download from my website,

[he uses ./mkprof -s and ./art -f -a ]

Two commands, didn’t require loading the lkb.

The fftb software can be downloaded via svn and compiled, there may also be a binary, it can also be pulled out of the logon tree.

Luis: so there’s nothing stopping us from running a server and having people working on this in other location.

Woodley: nothing stopping you, no.

Command lines

Key Commands

./mkprof -s ../erg-1214/tsdb/gold/mrs /tmp/mrs-demo
./art -f -a '../ace/ace --disable-generalization -g ../ace/erg-1214.dat -O' /tmp/mrs-demo/
./fftb -g ../ace/erg-1214.dat /tmp/mrs-demo/ --browser --gold ../erg-1214/tsdb/gold/mrs
./ace -g erg-1214.dat -1f --rooted-derivations
./ace -g erg-1214.dat -1f --rooted-derivations --udx=leaf
./ace -g erg-1214.dat -1f --rooted-derivations --udx=all
./ace -g erg-1214.dat -1Tf --pcfg=all-treebanks-gp0.pcfg

Test Sentences (ungrammatical)

$ ./ace -g erg-1214.dat -l --pcfg=all-treebanks-gp0.pcfg
        I usually small talk with my friend and classmate.
        I am want to see you.
        If anyone help customer, it is a little easier.

A Sample Treebanking

libtsdb $ ./mkprof
usage: ./mkprof [ OPTIONS ] destination
  -v   show version
  -h   show usage information
mkprof -s source  destination
   creates the 'destination' profile by copying
   the 'item' and 'relations' files from the source
   profile/skeleton (as well as item-set and fold,
   if present).  empty files are created for all
   other defined relations.
mkprof -r relations_file  [ -i input.txt ]  destination
   creates the 'destination' profile by copying
   the 'relations' file, populates an 'item' file
   with a record for each line in 'input.txt' if
   specified, or each line of <stdin>.  empty files
   are created for all other defined relations.
libtsdb $ ./mkprof -s ../erg-1214
erg-1214/        erg-1214-bridge/ 
libtsdb $ ./mkprof -s ../erg-1214
erg-1214/        erg-1214-bridge/ 
libtsdb $ ./mkprof -s ../erg-1214/tsdb/gold/mrs /tmp/mrs-demo
9746  bytes     relations
2303  bytes     item.gz
433   bytes     item-set.gz
0     bytes     fold
0     bytes     analysis
0     bytes     phenomenon
0     bytes     parameter
0     bytes     set
0     bytes     item-phenomenon
0     bytes     run
0     bytes     parse
0     bytes     result
0     bytes     rule
0     bytes     output
0     bytes     edge
0     bytes     tree
0     bytes     decision
0     bytes     preference
0     bytes     update
0     bytes     score
libtsdb $ ./art -f -a '../ace/ace -g ../ace/erg-1214.dat -O' /tmp/mrs-demo/
reading results for               11    0 results
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libtsdb $ vi /tmp/mrs-demo/edge 
libtsdb $ # ./mkprof -s ../erg-1214/tsdb/gold/mrs /tmp/mrs-demo
libtsdb $ # ./art -f -a '../ace/ace -g ../ace/erg-1214.dat -O' /tmp/mrs-demo/
libtsdb $ ./art -f -a '../ace/ace -g ../ace/erg-1214.dat -O' /tmp/mrs-demo/
libtsdb $ cd ../fftb
fftb $ cd ../ace
ace $ ./ace -g erg-1214.dat -1f --rooted-derivations
Dogs smile at cats.
SENT: Dogs smile at cats.
[ LTOP: h0
INDEX: e2 [ e SF: prop TENSE: pres MOOD: indicative PROG: - PERF: - ]
RELS: < [ udef_q<0:4> LBL: h4 ARG0: x3 [ x PERS: 3 NUM: pl IND: + ] RSTR: h5 BODY: h6 ]
 [ _dog_n_1<0:4> LBL: h7 ARG0: x3 ]
 [ _smile_v_at<5:10> LBL: h1 ARG0: e2 ARG1: x3 ARG2: x8 [ x PERS: 3 NUM: pl IND: + ] ]
 [ udef_q<14:19> LBL: h9 ARG0: x8 RSTR: h10 BODY: h11 ]
 [ _cat_n_1<14:19> LBL: h12 ARG0: x8 ] >
HCONS: < h0 qeq h1 h5 qeq h7 h10 qeq h12 > ] ;  (root_strict (1099 sb-hd_mc_c 4.272374 0 4 (1092 hdn_bnp_c 0.143203 0 1 (1091 n_pl_olr 1.086701 0 1 (82 dog_n1 0.000000 0 1 ("dogs" 58 "token [ +FORM \"dogs\" +FROM \"0\" +TO \"4\" +ID *diff-list* [ LIST *list* LAST *list* ] +TNT null_tnt [ +TAGS *null* +PRBS *null* +MAIN tnt_main [ +TAG \"NNS\" +PRB \"1.0\" ] ] +CLASS alphabetic [ +INITIAL + +CASE capitalized+lower ] +TRAIT token_trait [ +UW - +IT italics +LB bracket_null +RB bracket_null +HD token_head [ +LL ctype [ -CTYPE- string ] +TG string +TI \"0\" ] ] +PRED predsort +CARG \"Dogs\" +TICK bool ]")))) (1098 hd-cmp_u_c 3.015372 1 4 (1093 v_n3s-bse_ilr 0.571051 1 2 (63 smile_at_v1 0.000000 1 2 ("smile" 50 "token [ +FORM \"smile\" +FROM \"5\" +TO \"10\" +ID *diff-list* [ LIST *list* LAST *list* ] +TNT null_tnt [ +TAGS *null* +PRBS *null* +MAIN tnt_main [ +TAG \"NN\" +PRB \"1.0\" ] ] +CLASS alphabetic [ +INITIAL - +CASE non_capitalized+lower ] +TRAIT token_trait [ +UW - +IT italics +LB bracket_null +RB bracket_null +HD token_head [ +LL ctype [ -CTYPE- string ] +TG string +TI \"5\" ] ] +PRED predsort +CARG \"smile\" +TICK bool ]"))) (1097 hd-cmp_u_c 1.306115 2 4 (67 at_prtcl 0.430778 2 3 ("at" 52 "token [ +FORM \"at\" +FROM \"11\" +TO \"13\" +ID *diff-list* [ LIST *list* LAST *list* ] +TNT null_tnt [ +TAGS *null* +PRBS *null* +MAIN tnt_main [ +TAG \"IN\" +PRB \"1.0\" ] ] +CLASS alphabetic [ +INITIAL - +CASE non_capitalized+lower ] +TRAIT token_trait [ +UW - +IT italics +LB bracket_null +RB bracket_null +HD token_head [ +LL ctype [ -CTYPE- string ] +TG string +TI \"11\" ] ] +PRED predsort +CARG \"at\" +TICK bool ]")) (1096 hdn_bnp_c 0.242672 3 4 (1095 w_period_plr 0.614374 3 4 (1094 n_pl_olr 0.997276 3 4 (69 cat_n1 0.000000 3 4 ("cats." 54 "token [ +FORM \"cats.\" +FROM \"14\" +TO \"19\" +ID *diff-list* [ LIST *list* LAST *list* ] +TNT null_tnt [ +TAGS *null* +PRBS *null* +MAIN tnt_main [ +TAG \"NNS\" +PRB \"1.0\" ] ] +CLASS alphabetic [ +INITIAL - +CASE non_capitalized+lower ] +TRAIT token_trait [ +UW - +IT italics +LB bracket_null +RB bracket_null +HD token_head [ +LL ctype [ -CTYPE- string ] +TG string +TI \"14\" ] ] +PRED predsort +CARG \"cats\" +TICK bool ]")))))))))
NOTE: 1 readings, added 900 / 189 edges to chart (69 fully instantiated, 85 actives used, 50 passives used)     RAM: 1788k


NOTE: parsed 1 / 1 sentences, avg 1788k, time 0.14727s
ace $ ./ace -g erg-1214.dat -1f --rooted-derivations --udx=leaf
The dog slept.
SENT: The dog slept.
[ LTOP: h0
INDEX: e2 [ e SF: prop TENSE: past MOOD: indicative PROG: - PERF: - ]
RELS: < [ _the_q<0:3> LBL: h4 ARG0: x3 [ x PERS: 3 NUM: sg IND: + ] RSTR: h5 BODY: h6 ]
 [ _dog_n_1<4:7> LBL: h7 ARG0: x3 ]
 [ _sleep_v_1<8:14> LBL: h1 ARG0: e2 ARG1: x3 ] >
HCONS: < h0 qeq h1 h5 qeq h7 > ] ;  (root_strict (721 sb-hd_mc_c 0.818283 0 3 (718 sp-hd_n_c 0.997967 0 2 (66 the_1@d_-_the_le -0.486623 0 1 ("the" 46 "token [ +FORM \"the\" +FROM \"0\" +TO \"3\" +ID *diff-list* [ LIST *list* LAST *list* ] +TNT null_tnt [ +TAGS *null* +PRBS *null* +MAIN tnt_main [ +TAG \"DT\" +PRB \"1.0\" ] ] +CLASS alphabetic [ +INITIAL + +CASE capitalized+lower ] +TRAIT token_trait [ +UW - +IT italics +LB bracket_null +RB bracket_null +HD token_head [ +LL ctype [ -CTYPE- string ] +TG string +TI \"0\" ] ] +PRED predsort +CARG \"The\" +TICK bool ]")) (717 n_sg_ilr 1.169754 1 2 (50 dog_n1@n_-_c_le 0.031966 1 2 ("dog" 41 "token [ +FORM \"dog\" +FROM \"4\" +TO \"7\" +ID *diff-list* [ LIST *list* LAST *list* ] +TNT null_tnt [ +TAGS *null* +PRBS *null* +MAIN tnt_main [ +TAG \"NN\" +PRB \"1.0\" ] ] +CLASS alphabetic [ +INITIAL - +CASE non_capitalized+lower ] +TRAIT token_trait [ +UW - +IT italics +LB bracket_null +RB bracket_null +HD token_head [ +LL ctype [ -CTYPE- string ] +TG string +TI \"4\" ] ] +PRED predsort +CARG \"dog\" +TICK bool ]")))) (720 w_period_plr -0.219947 2 3 (719 v_pst_olr -0.106307 2 3 (54 sleep_v1@v_-_le 0.000000 2 3 ("slept." 43 "token [ +FORM \"slept.\" +FROM \"8\" +TO \"14\" +ID *diff-list* [ LIST *list* LAST *list* ] +TNT null_tnt [ +TAGS *null* +PRBS *null* +MAIN tnt_main [ +TAG \"VBD\" +PRB \"1.0\" ] ] +CLASS alphabetic [ +INITIAL - +CASE non_capitalized+lower ] +TRAIT token_trait [ +UW - +IT italics +LB bracket_null +RB bracket_null +HD token_head [ +LL ctype [ -CTYPE- string ] +TG string +TI \"8\" ] ] +PRED predsort +CARG \"slept\" +TICK bool ]"))))))
NOTE: 1 readings, added 542 / 46 edges to chart (19 fully instantiated, 30 actives used, 10 passives used)      RAM: 1068k


NOTE: parsed 1 / 1 sentences, avg 1068k, time 0.04985s
ace $ ./ace -g erg-1214.dat -1f --rooted-derivations --udx=all
The dog slept.
SENT: The dog slept.
[ LTOP: h0
INDEX: e2 [ e SF: prop TENSE: past MOOD: indicative PROG: - PERF: - ]
RELS: < [ _the_q<0:3> LBL: h4 ARG0: x3 [ x PERS: 3 NUM: sg IND: + ] RSTR: h5 BODY: h6 ]
 [ _dog_n_1<4:7> LBL: h7 ARG0: x3 ]
 [ _sleep_v_1<8:14> LBL: h1 ARG0: e2 ARG1: x3 ] >
HCONS: < h0 qeq h1 h5 qeq h7 > ] ;  (root_strict (721 sb-hd_mc_c@subjh_mc_rule 0.818283 0 3 (718 sp-hd_n_c@hspec_rule 0.997967 0 2 (66 the_1@d_-_the_le -0.486623 0 1 ("the" 46 "token [ +FORM \"the\" +FROM \"0\" +TO \"3\" +ID *diff-list* [ LIST *list* LAST *list* ] +TNT null_tnt [ +TAGS *null* +PRBS *null* +MAIN tnt_main [ +TAG \"DT\" +PRB \"1.0\" ] ] +CLASS alphabetic [ +INITIAL + +CASE capitalized+lower ] +TRAIT token_trait [ +UW - +IT italics +LB bracket_null +RB bracket_null +HD token_head [ +LL ctype [ -CTYPE- string ] +TG string +TI \"0\" ] ] +PRED predsort +CARG \"The\" +TICK bool ]")) (717 n_sg_ilr@n_sg_inflrule 1.169754 1 2 (50 dog_n1@n_-_c_le 0.031966 1 2 ("dog" 41 "token [ +FORM \"dog\" +FROM \"4\" +TO \"7\" +ID *diff-list* [ LIST *list* LAST *list* ] +TNT null_tnt [ +TAGS *null* +PRBS *null* +MAIN tnt_main [ +TAG \"NN\" +PRB \"1.0\" ] ] +CLASS alphabetic [ +INITIAL - +CASE non_capitalized+lower ] +TRAIT token_trait [ +UW - +IT italics +LB bracket_null +RB bracket_null +HD token_head [ +LL ctype [ -CTYPE- string ] +TG string +TI \"4\" ] ] +PRED predsort +CARG \"dog\" +TICK bool ]")))) (720 w_period_plr@punctuation_period_rule -0.219947 2 3 (719 v_pst_olr@v_pst_inflrule -0.106307 2 3 (54 sleep_v1@v_-_le 0.000000 2 3 ("slept." 43 "token [ +FORM \"slept.\" +FROM \"8\" +TO \"14\" +ID *diff-list* [ LIST *list* LAST *list* ] +TNT null_tnt [ +TAGS *null* +PRBS *null* +MAIN tnt_main [ +TAG \"VBD\" +PRB \"1.0\" ] ] +CLASS alphabetic [ +INITIAL - +CASE non_capitalized+lower ] +TRAIT token_trait [ +UW - +IT italics +LB bracket_null +RB bracket_null +HD token_head [ +LL ctype [ -CTYPE- string ] +TG string +TI \"8\" ] ] +PRED predsort +CARG \"slept\" +TICK bool ]"))))))
NOTE: 1 readings, added 542 / 46 edges to chart (19 fully instantiated, 30 actives used, 10 passives used)      RAM: 1068k


NOTE: parsed 1 / 1 sentences, avg 1068k, time 0.02070s
ace $ cd ../fftb
fftb $ ./fftb 
usage:  ./fftb -g grammar.dat [--gold profile_path [--auto]] [--browser [firefox]] [--webdir web_path] profile_path
fftb $ ./fftb -g ../ace/erg-1214.dat /tmp/mrs-demo/
grammar image: ../ace/erg-1214.dat
listening on http://127.0.0.1:9080/private/
should GET    /private/
should GET    /favicon.ico
should GET    /favicon.ico
should GET    /favicon.ico
should GET    /private/parse?profile=/&id=71
item id 71 -> input 'Abrams bet Browne a cigarette that it rained.'
profile parse id 71
-> loaded stored forest
found stored forest (25 edges connected to 1 roots).<br/>
UCSTAT: input 25 edges, output 17 edges
should GET    /private/session?0
should GET    /private/assets/render.js
should GET    /private/assets/control.js
should POST    /session?0;1;;
should POST    /session?0;0;;v_pst_olr@v_np-np-cp_le:=:1-2:0&_olddecs=
constraint: v_pst_olr@v_np-np-cp_le [1-2] type 2
should POST    /comment?0&
writing tsdb relation 'tree' with 1 tuples
should POST    /session?0;0;;v_pst_olr@v_np-np-cp_le:=:1-2:0&_olddecs=
constraint: v_pst_olr@v_np-np-cp_le [1-2] type 2
should POST    /save?0&accepted=1
writing tsdb relation 'decision' with 1 tuples
remaining = 1 [1 decisions used]
date string: 03-01-2017 17:04:54
date string: 03-01-2017 17:05:03
writing tsdb relation 'tree' with 1 tuples
writing tsdb relation 'result' with 1 tuples
writing tsdb relation 'preference' with 1 tuples
writing tsdb relation 'parse' with 107 tuples
should GET    /private/next_unannotated?0
old item id '71' + dir 1 = new item id '81'
should GET    /private/parse?profile=/&id=81
item id 81 -> input 'Abrams knew that it rained.'
profile parse id 81
-> loaded stored forest
found stored forest (14 edges connected to 1 roots).<br/>
UCSTAT: input 14 edges, output 9 edges
should GET    /private/session?1
should GET    /private/assets/render.js
should GET    /private/assets/control.js
should POST    /session?1;1;;
^CTIMERS (0 calls = ~ 0.0µs overhead):
fftb $ 
fftb $ 
fftb $ 
fftb $ ./fftb -g ../ace/erg-1214.dat /tmp/mrs-demo/ --browser
grammar image: ../ace/erg-1214.dat
listening on http://127.0.0.1:59552/private/
should GET    /private/
should GET    /favicon.ico
should GET    /favicon.ico
should GET    /favicon.ico
should GET    /private/exit
TIMERS (0 calls = ~ 0.0µs overhead):
fftb $ ./fftb -g ../ace/erg-1214.dat /tmp/mrs-demo/ --browser --gold ../erg-1214/tsdb/gold/mrs
grammar image: ../ace/erg-1214.dat
Just one TSDB profile: /tmp/mrs-demo/
Would update from profile: ../erg-1214/tsdb/gold/mrs
listening on http://127.0.0.1:59559/private/
should GET    /private/
should GET    /favicon.ico
should GET    /favicon.ico
should GET    /favicon.ico
should GET    /private/update?/
[11]    {0 decisions}   UCSTAT: input 5 edges, output 3 edges
{3 edges}       {1 / 1 trees active}    identical       ... saving this tree as preferred, with decisions from goldwriting tsdb relation 'decision' with 1 tuples
writing tsdb relation 'tree' with 2 tuples
writing tsdb relation 'result' with 2 tuples
writing tsdb relation 'preference' with 2 tuples
writing tsdb relation 'parse' with 107 tuples
 [ success ]
[21]    {0 decisions}   UCSTAT: input 7 edges, output 3 edges
{3 edges}       {1 / 1 trees active}    identical       ... saving this tree as preferred, with decisions from goldwriting tsdb relation 'decision' with 1 tuples
writing tsdb relation 'tree' with 3 tuples
writing tsdb relation 'result' with 3 tuples
writing tsdb relation 'preference' with 3 tuples
writing tsdb relation 'parse' with 107 tuples
 [ success ]
[31]    {7 decisions}   UCSTAT: input 17 edges, output 8 edges
{8 edges}       {1 / 2 trees active}    identical       ... saving this tree as preferred, with decisions from goldwriting tsdb relation 'decision' with 8 tuples
writing tsdb relation 'tree' with 4 tuples
writing tsdb relation 'result' with 4 tuples
writing tsdb relation 'preference' with 4 tuples
writing tsdb relation 'parse' with 107 tuples
 [ success ]
[41]    {7 decisions}   UCSTAT: input 18 edges, output 12 edges
{12 edges}      {1 / 3 trees active}    identical       ... saving this tree as preferred, with decisions from goldwriting tsdb relation 'decision' with 15 tuples
writing tsdb relation 'tree' with 5 tuples
writing tsdb relation 'result' with 5 tuples
writing tsdb relation 'preference' with 5 tuples
writing tsdb relation 'parse' with 107 tuples
 [ success ]
[51]    {10 decisions}  UCSTAT: input 31 edges, output 20 edges
{20 edges}      {1 / 3 trees active}    identical       ... saving this tree as preferred, with decisions from goldwriting tsdb relation 'decision' with 25 tuples
writing tsdb relation 'tree' with 6 tuples
writing tsdb relation 'result' with 6 tuples
writing tsdb relation 'preference' with 6 tuples
writing tsdb relation 'parse' with 107 tuples
 [ success ]
[61]    {0 decisions}   UCSTAT: input 19 edges, output 11 edges
{11 edges}      {1 / 1 trees active}    identical       ... saving this tree as preferred, with decisions from goldwriting tsdb relation 'decision' with 25 tuples
writing tsdb relation 'tree' with 7 tuples
writing tsdb relation 'result' with 7 tuples
writing tsdb relation 'preference' with 7 tuples
writing tsdb relation 'parse' with 107 tuples
 [ success ]
[81]    {0 decisions}   UCSTAT: input 14 edges, output 9 edges
{9 edges}       {1 / 1 trees active}    identical       ... saving this tree as preferred, with decisions from goldwriting tsdb relation 'decision' with 25 tuples
writing tsdb relation 'tree' with 8 tuples
writing tsdb relation 'result' with 8 tuples
writing tsdb relation 'preference' with 8 tuples
writing tsdb relation 'parse' with 107 tuples
 [ success ]
[91]    {15 decisions}  UCSTAT: input 30 edges, output 21 edges
{21 edges}      {1 / 4 trees active}    identical       ... saving this tree as preferred, with decisions from goldwriting tsdb relation 'decision' with 40 tuples
writing tsdb relation 'tree' with 9 tuples
writing tsdb relation 'result' with 9 tuples
writing tsdb relation 'preference' with 9 tuples
writing tsdb relation 'parse' with 107 tuples
 [ success ]
[101]   {22 decisions}  UCSTAT: input 53 edges, output 42 edges
{42 edges}      {1 / 14 trees active}   identical       ... saving this tree as preferred, with decisions from goldwriting tsdb relation 'decision' with 62 tuples
writing tsdb relation 'tree' with 10 tuples
writing tsdb relation 'result' with 10 tuples
writing tsdb relation 'preference' with 10 tuples
writing tsdb relation 'parse' with 107 tuples
 [ success ]
[111]   {0 decisions}   UCSTAT: input 8 edges, output 5 edges
{5 edges}       {1 / 1 trees active}    identical       ... saving this tree as preferred, with decisions from goldwriting tsdb relation 'decision' with 62 tuples
writing tsdb relation 'tree' with 11 tuples
writing tsdb relation 'result' with 11 tuples
writing tsdb relation 'preference' with 11 tuples
writing tsdb relation 'parse' with 107 tuples
 [ success ]
[121]   {13 decisions}  UCSTAT: input 27 edges, output 16 edges
{16 edges}      {1 / 2 trees active}    identical       ... saving this tree as preferred, with decisions from goldwriting tsdb relation 'decision' with 75 tuples
writing tsdb relation 'tree' with 12 tuples
writing tsdb relation 'result' with 12 tuples
writing tsdb relation 'preference' with 12 tuples
writing tsdb relation 'parse' with 107 tuples
 [ success ]
[131]   {0 decisions}   UCSTAT: input 8 edges, output 5 edges
{5 edges}       {1 / 1 trees active}    identical       ... saving this tree as preferred, with decisions from goldwriting tsdb relation 'decision' with 75 tuples
writing tsdb relation 'tree' with 13 tuples
writing tsdb relation 'result' with 13 tuples
writing tsdb relation 'preference' with 13 tuples
writing tsdb relation 'parse' with 107 tuples
 [ success ]
[141]   {0 decisions}   UCSTAT: input 6 edges, output 3 edges
{3 edges}       {1 / 1 trees active}    identical       ... saving this tree as preferred, with decisions from goldwriting tsdb relation 'decision' with 75 tuples
writing tsdb relation 'tree' with 14 tuples
writing tsdb relation 'result' with 14 tuples
writing tsdb relation 'preference' with 14 tuples
writing tsdb relation 'parse' with 107 tuples
 [ success ]
[151]   {0 decisions}   UCSTAT: input 11 edges, output 7 edges
{7 edges}       {1 / 1 trees active}    identical       ... saving this tree as preferred, with decisions from goldwriting tsdb relation 'decision' with 75 tuples
writing tsdb relation 'tree' with 15 tuples
writing tsdb relation 'result' with 15 tuples
writing tsdb relation 'preference' with 15 tuples
writing tsdb relation 'parse' with 107 tuples
 [ success ]
[161]   {13 decisions}  UCSTAT: input 25 edges, output 17 edges
{17 edges}      {1 / 4 trees active}    identical       ... saving this tree as preferred, with decisions from goldwriting tsdb relation 'decision' with 88 tuples
writing tsdb relation 'tree' with 16 tuples
writing tsdb relation 'result' with 16 tuples
writing tsdb relation 'preference' with 16 tuples
writing tsdb relation 'parse' with 107 tuples
 [ success ]
[171]   {23 decisions}  UCSTAT: input 47 edges, output 32 edges
{32 edges}      {1 / 9 trees active}    identical       ... saving this tree as preferred, with decisions from goldwriting tsdb relation 'decision' with 111 tuples
writing tsdb relation 'tree' with 17 tuples
writing tsdb relation 'result' with 17 tuples
writing tsdb relation 'preference' with 17 tuples
writing tsdb relation 'parse' with 107 tuples
 [ success ]
[181]   {0 decisions}   UCSTAT: input 6 edges, output 3 edges
{3 edges}       {1 / 1 trees active}    identical       ... saving this tree as preferred, with decisions from goldwriting tsdb relation 'decision' with 111 tuples
writing tsdb relation 'tree' with 18 tuples
writing tsdb relation 'result' with 18 tuples
writing tsdb relation 'preference' with 18 tuples
writing tsdb relation 'parse' with 107 tuples
 [ success ]
[191]   {12 decisions}  UCSTAT: input 24 edges, output 11 edges
{11 edges}      {1 / 4 trees active}

Last update: 2017-01-05 by SanghounSong [edit]