Alias transfer

app/lib/docview.js

@@ -451,7 +451,7 @@ export class DocumentViewer extends Component {
   }
 
   BuildPanel(phrase, fidx) {
-    let mention = this.document.frames[fidx];
+    let frame = this.document.frames[fidx];
     let panel = document.createElement("div");
     panel.className = "panel";
     panel.id = "p" + next_panel++;
@@ -462,9 +462,11 @@ export class DocumentViewer extends Component {
 
     let title = document.createElement("span");
     title.className = "panel-title";
-    title.appendChild(document.createTextNode(phrase));
-    titlebar.appendChild(title);
-    this.AddTypes(titlebar, mention.types);
+    if (phrase) {
+      title.appendChild(document.createTextNode(phrase));
+      titlebar.appendChild(title);
+      this.AddTypes(titlebar, frame.types);
+    }
 
     let icon = document.createElement("span");
     icon.className = "panel-icon";
@@ -476,19 +478,24 @@ export class DocumentViewer extends Component {
     let contents = document.createElement("div");
     contents.className = "panel-content"
 
-    let slots = mention.slots;
-    if (slots) {
-      for (let i = 0; i < slots.length; i += 2) {
-        let n = slots[i];
-        let v = slots[i + 1];
-        if (this.document.frames[n].id == "evokes" ||
-            this.document.frames[n].id == "is") {
-          let avm = this.BuildAVM(v, {});
-          contents.appendChild(avm);
+    if (phrase) {
+      let rendered = {};
+      let slots = frame.slots;
+      if (slots) {
+        for (let i = 0; i < slots.length; i += 2) {
+          let n = slots[i];
+          let v = slots[i + 1];
+          if (this.document.frames[n].id == "evokes" ||
+              this.document.frames[n].id == "is") {
+            let avm = this.BuildAVM(v, rendered);
+            contents.appendChild(avm);
+          }
         }
       }
+    } else {
+      let avm = this.BuildAVM(fidx, {});
+      contents.appendChild(avm);
     }
-
     panel.appendChild(contents);
     return panel;
   }
@@ -504,7 +511,11 @@ export class DocumentViewer extends Component {
     let span = e.currentTarget;
     let phrase = span.getAttribute("phrase");
     let fidx = parseInt(span.getAttribute("frame"));
-    this.AddPanel('"' + phrase + '"', fidx);
+    if (phrase) {
+      this.AddPanel('"' + phrase + '"', fidx);
+    } else {
+      this.AddPanel(null, fidx);
+    }
   }
 
   ClosePanel(e) {
@@ -519,7 +530,6 @@ export class DocumentViewer extends Component {
     chip.className = "chip";
     chip.id = "t" + fidx;
     chip.setAttribute("frame", fidx);
-    chip.setAttribute("phrase", name);
     chip.appendChild(document.createTextNode(name));
 
     return chip;
@@ -548,13 +558,14 @@ export class DocumentViewer extends Component {
 
     let fidx = parseInt(span.getAttribute("frame"))
     let mention = this.document.frames[fidx];
+    let rendered = {};
     let slots = mention.slots;
     if (slots) {
       for (let i = 0; i < slots.length; i += 2) {
         let n = slots[i];
         let v = slots[i + 1];
         if (this.document.frames[n].id == "evokes") {
-          let avm = this.BuildAVM(v, {});
+          let avm = this.BuildAVM(v, rendered);
           callout.appendChild(avm);
         }
       }

data/wiki/calendar.sling

@@ -211,7 +211,7 @@
     625: Q2662
     626: Q2661
     627: Q2664
-    628: Q2664
+    628: Q2660
     629: Q2659
     630: Q2657
 

doc/guide/install.md

@@ -43,7 +43,7 @@ SLING uses [Bazel](https://bazel.build/) as the build system, so you need to
 to build the SLING parser.
 
 ```shell
-sudo apt-get install pkg-config zip g++ zlib1g-dev unzip python
+sudo apt-get install pkg-config zip g++ zlib1g-dev unzip python2.7 python2.7-dev
 wget -P /tmp https://github.com/bazelbuild/bazel/releases/download/0.13.0/bazel-0.13.0-installer-linux-x86_64.sh
 chmod +x /tmp/bazel-0.13.0-installer-linux-x86_64.sh
 sudo /tmp/bazel-0.13.0-installer-linux-x86_64.sh

doc/guide/myelin.md

@@ -377,7 +377,7 @@ flow = "flow" <version>
 
 var = <#flags> (IN=1, OUT=2, REF=4, LEARNABLE=8 UNIQUE=16, from version 5)
       <name$>
-      <#aliases> <alias$>
+      <#aliases> <alias$>*
       <dtype$>
       <shape>
       <#bytes> value
@@ -397,11 +397,11 @@ blob = <#flags> (unused, from version 5)
 
 func = <#flags> (TRAINING=1, from version 5)
        <name$>
-       <#ops> <op$>
+       <#ops> <op$>*
 
 cnx = <#flags> (unused, from version 5)
       <name$>
-      <#vars> <var$>
+      <#vars> <var$>*
 
 shape = <#dims> <size>*
 

python/run.py

@@ -120,37 +120,6 @@
              default=False,
              action='store_true')
 
-flags.define("--dryrun",
-             help="build worflows but do not run them",
-             default=False,
-             action='store_true')
-
-flags.define("--monitor",
-             help="port number for task monitor (0 means no monitor)",
-             default=6767,
-             type=int,
-             metavar="PORT")
-
-flags.define("--logdir",
-             help="directory where workflow logs are stored",
-             default="local/logs",
-             metavar="DIR")
-
-def run_workflow(wf):
-  # In dryrun mode the workflow is just dumped without running it.
-  if flags.arg.dryrun:
-    print wf.wf.dump()
-    return
-
-  # Start workflow.
-  log.info("start workflow")
-  wf.wf.start()
-
-  # Wait until workflow completes. Poll every second to make the workflow
-  # interruptible.
-  done = False
-  while not done: done = wf.wf.wait(1000)
-
 def download_corpora():
   if flags.arg.download_wikidata or flags.arg.download_wikipedia:
     wf = download.DownloadWorkflow("wiki-download")
@@ -164,7 +133,7 @@ def download_corpora():
       for language in flags.arg.languages:
         wf.download_wikipedia(language=language)
 
-    run_workflow(wf)
+    workflow.run(wf.wf)
 
 def import_wiki():
   if flags.arg.import_wikidata or flags.arg.import_wikipedia:
@@ -180,7 +149,7 @@ def import_wiki():
         log.info("Import " + language + " wikipedia")
         wf.wikipedia(language=language)
 
-    run_workflow(wf)
+    workflow.run(wf.wf)
 
 def parse_wikipedia():
   # Convert wikipedia pages to SLING documents.
@@ -189,36 +158,36 @@ def parse_wikipedia():
       log.info("Parse " + language + " wikipedia")
       wf = wiki.WikiWorkflow(language + "-wikipedia-parsing")
       wf.parse_wikipedia(language=language)
-      run_workflow(wf)
+      workflow.run(wf.wf)
 
 def fuse_items():
   # Merge categories from wikipedias.
   if flags.arg.merge_categories:
     log.info("Merge wikipedia categories")
     wf = wiki.WikiWorkflow("category-merging")
     wf.merge_wikipedia_categories()
-    run_workflow(wf)
+    workflow.run(wf.wf)
 
   # Invert categories.
   if flags.arg.invert_categories:
     log.info("Invert categories")
     wf = wiki.WikiWorkflow("category-inversion")
     wf.invert_wikipedia_categories()
-    run_workflow(wf)
+    workflow.run(wf.wf)
 
   # Compute item popularity.
   if flags.arg.compute_item_popularity:
     log.info("Compute item popularity")
     wf = wiki.WikiWorkflow("item-popularity")
     wf.compute_item_popularity()
-    run_workflow(wf)
+    workflow.run(wf.wf)
 
   # Fuse items.
   if flags.arg.fuse_items:
     log.info("Fuse items")
     wf = wiki.WikiWorkflow("fuse-items")
     wf.fuse_items()
-    run_workflow(wf)
+    workflow.run(wf.wf)
 
 
 def build_knowledge_base():
@@ -227,31 +196,31 @@ def build_knowledge_base():
     log.info("Build knowledge base repository")
     wf = wiki.WikiWorkflow("knowledge-base")
     wf.build_knowledge_base()
-    run_workflow(wf)
+    workflow.run(wf.wf)
 
   # Extract item names from wikidata and wikipedia.
   if flags.arg.extract_names:
     for language in flags.arg.languages:
       log.info("Extract " + language + " names")
       wf = wiki.WikiWorkflow(language + "-name-extraction")
       wf.extract_names(language=language)
-      run_workflow(wf)
+      workflow.run(wf.wf)
 
   # Build name table.
   if flags.arg.build_nametab:
     for language in flags.arg.languages:
       log.info("Build " + language + " name table")
       wf = wiki.WikiWorkflow(language + "-name-table")
       wf.build_name_table(language=language)
-      run_workflow(wf)
+      workflow.run(wf.wf)
 
   # Build phrase table.
   if flags.arg.build_phrasetab:
     for language in flags.arg.languages:
       log.info("Build " + language + " phrase table")
       wf = wiki.WikiWorkflow(language + "-phrase-table")
       wf.build_phrase_table(language=language)
-      run_workflow(wf)
+      workflow.run(wf.wf)
 
 def train_embeddings():
   # Extract vocabulary for word embeddings.
@@ -260,36 +229,36 @@ def train_embeddings():
       log.info("Extract " + language + " vocabulary")
       wf = embedding.EmbeddingWorkflow(language + "-vocabulary")
       wf.extract_vocabulary(language=language)
-      run_workflow(wf)
+      workflow.run(wf.wf)
 
   # Train word embeddings.
   if flags.arg.train_word_embeddings:
     for language in flags.arg.languages:
       log.info("Train " + language + " word embeddings")
       wf = embedding.EmbeddingWorkflow(language + "-word-embeddings")
       wf.train_word_embeddings(language=language)
-      run_workflow(wf)
+      workflow.run(wf.wf)
 
   # Extract vocabulary for fact and category embeddings.
   if flags.arg.extract_fact_lexicon:
     log.info("Extract fact and category lexicons")
     wf = embedding.EmbeddingWorkflow("fact-lexicon")
     wf.extract_fact_lexicon()
-    run_workflow(wf)
+    workflow.run(wf.wf)
 
   # Extract facts from knowledge base.
   if flags.arg.extract_facts:
     log.info("Extract facts from knowledge base")
     wf = embedding.EmbeddingWorkflow("fact-extraction")
     wf.extract_facts()
-    run_workflow(wf)
+    workflow.run(wf.wf)
 
   # Train fact and category embeddings.
   if flags.arg.train_fact_embeddings:
     log.info("Train fact and category embeddings")
     wf = embedding.EmbeddingWorkflow("fact-embeddings")
     wf.train_fact_embeddings()
-    run_workflow(wf)
+    workflow.run(wf.wf)
 
 
 if __name__ == '__main__':
@@ -309,20 +278,16 @@ def train_embeddings():
     flags.arg.build_nametab = True
     flags.arg.build_phrasetab = True
 
-  # Start task monitor.
-  if flags.arg.monitor > 0: workflow.start_monitor(flags.arg.monitor)
-
   # Run workflows.
+  workflow.startup()
   download_corpora()
   import_wiki()
   parse_wikipedia()
   fuse_items()
   build_knowledge_base()
   train_embeddings()
-
-  # Stop task monitor.
-  if flags.arg.monitor > 0: workflow.stop_monitor()
-  workflow.save_workflow_log(flags.arg.logdir)
+  workflow.shutdown()
 
   # Done.
   log.info("Done")
+

python/task/download.py

@@ -16,6 +16,7 @@
 
 import os
 import urllib2
+import _strptime
 import time
 
 from workflow import *

python/task/wiki.py

@@ -583,7 +583,7 @@ def extract_names(self, aliases=None, language=None):
     if aliases == None:
       # Get language-dependent aliases from Wikidata and Wikpedia.
       wikidata_aliases = self.wf.map(self.fused_items(),
-                                     "profile-alias-extractor",
+                                     "alias-extractor",
                                      params={
                                        "language": language,
                                        "skip_aux": True,
@@ -599,7 +599,7 @@ def extract_names(self, aliases=None, language=None):
     merged_aliases = self.wf.shuffle(aliases, len(names))
 
     # Filter and select aliases.
-    self.wf.reduce(merged_aliases, names, "profile-alias-reducer",
+    self.wf.reduce(merged_aliases, names, "alias-reducer",
                    params={"language": language})
     return names
 
@@ -648,8 +648,11 @@ def build_phrase_table(self, names=None, language=None):
     with self.wf.namespace("phrase-table"):
       builder = self.wf.task("phrase-table-builder")
       builder.add_param("language", language)
+      builder.add_param("transfer_aliases", True)
       self.wf.connect(self.wf.read(names, name="name-reader"), builder)
+      kb = self.knowledge_base()
       repo = self.phrase_table(language)
+      builder.attach_input("commons", kb)
       builder.attach_output("repository", repo)
     return repo