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sentence (string)relation (class label)
"The system as described above has its greatest application in an arrayed <e1>configuration</e1> of antenna <e2>elements</e2>."
3 (Component-Whole(e2,e1))
"The <e1>child</e1> was carefully wrapped and bound into the <e2>cradle</e2> by means of a cord."
18 (Other)
"The <e1>author</e1> of a keygen uses a <e2>disassembler</e2> to look at the raw assembly code."
11 (Instrument-Agency(e2,e1))
"A misty <e1>ridge</e1> uprises from the <e2>surge</e2>."
18 (Other)
"The <e1>student</e1> <e2>association</e2> is the voice of the undergraduate student population of the State University of New York at Buffalo."
12 (Member-Collection(e1,e2))
"This is the sprawling <e1>complex</e1> that is Peru's largest <e2>producer</e2> of silver."
18 (Other)
"The current view is that the chronic <e1>inflammation</e1> in the distal part of the stomach caused by Helicobacter pylori <e2>infection</e2> results in an increased acid production from the non-infected upper corpus region of the stomach."
1 (Cause-Effect(e2,e1))
"<e1>People</e1> have been moving back into <e2>downtown</e2>."
6 (Entity-Destination(e1,e2))
"The <e1>lawsonite</e1> was contained in a <e2>platinum crucible</e2> and the counter-weight was a plastic crucible with metal pieces."
4 (Content-Container(e1,e2))
"The solute was placed inside a beaker and 5 mL of the <e1>solvent</e1> was pipetted into a 25 mL glass <e2>flask</e2> for each trial."
6 (Entity-Destination(e1,e2))
"The fifty <e1>essays</e1> collected in this <e2>volume</e2> testify to most of the prominent themes from Professor Quispel's scholarly career."
12 (Member-Collection(e1,e2))
"Their <e1>composer</e1> has sunk into <e2>oblivion</e2>."
18 (Other)
"The Pulitzer Committee issues an official <e1>citation</e1> explaining the <e2>reasons</e2> for the award."
14 (Message-Topic(e1,e2))
"The <e1>burst</e1> has been caused by water hammer <e2>pressure</e2>."
1 (Cause-Effect(e2,e1))
"Even commercial <e1>networks</e1> have moved into <e2>high-definition broadcast</e2>."
11 (Instrument-Agency(e2,e1))
"It was a friendly <e1>call</e1> to remind them about the <e2>bill</e2> and make sure they have a copy of the invoice."
14 (Message-Topic(e1,e2))
"Texas-born <e1>virtuoso</e1> finds harmony, sophistication in Appalachian <e2>instrument</e2>."
11 (Instrument-Agency(e2,e1))
"The <e1>factory</e1>'s products have included flower pots, Finnish rooster-whistles, pans, <e2>trays</e2>, tea pots, ash trays and air moisturisers."
17 (Product-Producer(e2,e1))
"The girl showed a photo of apple <e1>tree</e1> <e2>blossom</e2> on a fruit tree in the Central Valley."
3 (Component-Whole(e2,e1))
"They tried an assault of their own an hour later, with two columns of sixteen tanks backed by a <e1>battalion</e1> of Panzer <e2>grenadiers</e2>."
13 (Member-Collection(e2,e1))
"Their <e1>knowledge</e1> of the power and rank symbols of the Continental empires was gained from the numerous Germanic <e2>recruits</e2> in the Roman army, and from the Roman practice of enfeoffing various Germanic warrior groups with land in the imperial provinces."
8 (Entity-Origin(e1,e2))
"She soon had a <e1>stable</e1> of her own rescued <e2>hounds</e2>."
13 (Member-Collection(e2,e1))
"The <e1>singer</e1>, who performed three of the nominated songs, also caused a <e2>commotion</e2> on the red carpet."
0 (Cause-Effect(e1,e2))
"His intellectually engaging books and <e1>essays</e1> remain pertinent to illuminating contemporary <e2>history</e2>."
18 (Other)
"Poor hygiene controls, reports of a <e1>brace</e1> of gamey <e2>grouse</e2> and what looked like a skinned fox all amounted to a pie that was unfit for human consumption."
13 (Member-Collection(e2,e1))
"This sweet <e1>dress</e1> is made with a <e2>blend</e2> of cotton and silk, and the crochet flower necklace is the perfect accessory."
18 (Other)
"<e1>Suicide</e1> is one of the leading causes of <e2>death</e2> among pre-adolescents and teens, and victims of bullying are at an increased risk for committing suicide."
0 (Cause-Effect(e1,e2))
"This <e1>article</e1> gives details on 2004 in <e2>music</e2> in the United Kingdom, including the official charts from that year."
14 (Message-Topic(e1,e2))
"We have therefore taken the initiative to convene the first international open <e1>meeting</e1> dedicated solely to <e2>rural history</e2>."
14 (Message-Topic(e1,e2))
"The <e1>timer</e1> of the <e2>device</e2> automatically eliminates wasted "standby power" consumption by automatically turn off electronics plugged into the "auto off" outlets."
2 (Component-Whole(e1,e2))
"Bob Parks made a similar <e1>offer</e1> in a <e2>phone call</e2> made earlier this week."
15 (Message-Topic(e2,e1))
"He had chest pains and <e1>headaches</e1> from <e2>mold</e2> in the bedrooms."
1 (Cause-Effect(e2,e1))
"The silver-haired author was not just laying India's politician saint to rest but healing a generations-old rift in the family of the <e1>country</e1>'s founding <e2>father</e2>."
16 (Product-Producer(e1,e2))
"It describes a method for loading a horizontal <e1>stack</e1> of containers into a <e2>carton</e2>."
6 (Entity-Destination(e1,e2))
"The Foundation decided to repurpose the building in order to reduce wear and tear on the <e1>plumbing</e1> in the <e2>manor house</e2> by redirecting visitors during restoration projects and beyond."
2 (Component-Whole(e1,e2))
"The technology is available to produce and transmit <e1>electricity</e1> economically from OTEC <e2>systems</e2>."
8 (Entity-Origin(e1,e2))
"The Medicare buy-in <e1>plan</e1> ran into Senate <e2>resistance</e2>."
18 (Other)
"The <e1>provinces</e1> are divided into <e2>counties</e2> (shahrestan), and subdivided into districts (bakhsh) and sub-districts (dehestan)."
3 (Component-Whole(e2,e1))
"Financial <e1>stress</e1> is one of the main causes of <e2>divorce</e2>."
0 (Cause-Effect(e1,e2))
"<e1>Newspapers</e1> swap content via widgets with the help of the newsgator <e2>service</e2>."
11 (Instrument-Agency(e2,e1))
"The <e1>women</e1> that caused the <e2>accident</e2> was on the cell phone and ran thru the intersection without pausing on the median."
0 (Cause-Effect(e1,e2))
"The <e1>transmitter</e1> was discovered inside a bed settee <e2>suite</e2> on which he had been sitting."
4 (Content-Container(e1,e2))
"The Kerala backwaters are a <e1>chain</e1> of brackish <e2>lagoons</e2> and lakes lying parallel to the Arabian Sea coast of Kerala state in southern India."
13 (Member-Collection(e2,e1))
"A St. Paul College <e1>student</e1> was released from <e2>jail</e2> Wednesday night, after his arrest Tuesday in the alleged rape of another student on campus."
8 (Entity-Origin(e1,e2))
"<e1>Calluses</e1> are caused by improperly fitting shoes or by a <e2>skin abnormality</e2>."
1 (Cause-Effect(e2,e1))
"<e1>Adults</e1> use <e2>drugs</e2> for this purpose."
11 (Instrument-Agency(e2,e1))
"The <e1>councilor</e1> proposed assessing infinitival complements through <e2>elicitation</e2>."
11 (Instrument-Agency(e2,e1))
"As in the popular movie "Deep Impact", the action of the Perseid <e1>meteor shower</e1> is caused by a <e2>comet</e2>, in this case periodic comet Swift-Tuttle."
1 (Cause-Effect(e2,e1))
"The following information appeared in the <e1>notes</e1> to consolidated financial <e2>statements</e2> of some corporate annual reports."
18 (Other)
"HipHop appropriates the symbols of a consumer society: oversized <e1>diamond</e1> <e2>colliers</e2> are worn."
18 (Other)
"The <e1>radiation</e1> from the atomic <e2>bomb explosion</e2> is a typical acute radiation."
1 (Cause-Effect(e2,e1))
"The ride-on <e1>boat</e1> <e2>tiller</e2> was developed by engineers Arnold S. Juliano and Dr. Eulito U. Bautista."
3 (Component-Whole(e2,e1))
"A neoplastic <e1>recurrence</e1> arose from an extensive <e2>radiation</e2> induced ulceration."
1 (Cause-Effect(e2,e1))
"He has a tattoo on his right arm and <e1>scars</e1> from <e2>stitches</e2> on his right elbow."
1 (Cause-Effect(e2,e1))
"Whether your home includes a charm of finches, a sute of bloodhounds, or a <e1>knob</e1> of <e2>toads</e2>, I think it's important to keep the numbers within reason."
13 (Member-Collection(e2,e1))
"Furthermore, these INGO practitioners constructed a <e1>discourse</e1> around <e2>participation</e2> which distorted the real significance of participation."
14 (Message-Topic(e1,e2))
"Kelvin bought a <e1>silver</e1> <e2>ring</e2> which he was so happy with and he keeps wearing it now even though its abit too big haha."
18 (Other)
"Scientists are in the midst of an ongoing <e1>debate</e1> about the relative <e2>value</e2> of openness and collaboration in their profession."
14 (Message-Topic(e1,e2))
"This cut blue and white striped cotton <e1>dress</e1> with red bands on the bodice was in a <e2>trunk</e2> of vintage Barbie clothing."
4 (Content-Container(e1,e2))
"My major <e1>disagreement</e1> with Lyons concerns the <e2>causal part</e2> of his theory."
18 (Other)
"Both his <e1>feet</e1> have been moving into the <e2>ball</e2>."
6 (Entity-Destination(e1,e2))
"The scissors were in a small plastic soap container, next to a bar of soap, and the <e1>box cutters</e1> were in a <e2>box</e2> next to a bottle of after-shave lotion."
4 (Content-Container(e1,e2))
"A great <e1>wing</e1> of fluorite <e2>dragons</e2>, the greatest concentration of the rather solitary dragons ever known, joined the desperate battle with the blues and silvers against Chaos."
13 (Member-Collection(e2,e1))
"As a control, <e1>cowpea</e1> was sealed in <e2>double bags</e2> without fumigant."
6 (Entity-Destination(e1,e2))
"The infectious bacterial disease <e1>brucellosis</e1> has been found in a beef <e2>cow</e2> in eastern Idaho."
18 (Other)
"As the Anglo-Norman force sustained but little loss in this battle, their archers at the onset showered a hail of arrows upon the Irish host who were not protected with mail armour, and shot them down in hundreds before they could get to close quarters; and then the charge of the heavy Anglo-Norman cavalry of mail-clad knights, completed the havoc and <e1>rout</e1> of the undisciplined Gaelic <e2>hosts</e2>."
18 (Other)
"The first incarnation of this series was set in the 1940s, during World War II, when the <e1>princess</e1> left her native paradise <e2>island</e2> (where Amazon women had lived for centuries) to help the U.S. foil the Nazis."
8 (Entity-Origin(e1,e2))
"Cieply's <e1>story</e1> makes a compelling <e2>point</e2> about modern-day studio economics."
14 (Message-Topic(e1,e2))
"We poured the <e1>milk</e1> into the <e2>pumpkin mixture</e2>."
6 (Entity-Destination(e1,e2))
"Lawyers in Detroit also worked overtime as several <e1>lawsuits</e1> ensued from angry and injured <e2>fans</e2>."
8 (Entity-Origin(e1,e2))
"The continuing Nigerian <e1>outbreak</e1> is the biggest ever caused by the <e2>vaccine</e2>."
1 (Cause-Effect(e2,e1))
"Our mercenary Army has now degenerated into a Godless <e1>cabal</e1> of mindless <e2>killers</e2> not unlike the Soviets that were butchering civilians in Afghanistan (exactly as sadistically as we have)."
13 (Member-Collection(e2,e1))
"The <e1>fire</e1> inside WTC was caused by exploding <e2>fuel</e2>."
1 (Cause-Effect(e2,e1))
"The <e1>epithelium</e1> from the knockout mouse bladder is migrating into the transplanted <e2>matrix</e2>."
6 (Entity-Destination(e1,e2))
"The <e1>staff</e1> was removed from his <e2>position</e2>."
8 (Entity-Origin(e1,e2))
"The <e1>suffering</e1> caused by the <e2>terrorists</e2> is the real torture."
1 (Cause-Effect(e2,e1))
"This <e1>love</e1> of nature's gift has been reflected in <e2>artworks</e2> dating back more than a thousand years."
15 (Message-Topic(e2,e1))
"The <e1>court</e1> decided the objection by making the instalment <e2>order</e2> as sought."
17 (Product-Producer(e2,e1))
"In a poetic twist, the <e1>tsunami</e1> triggered by the rock <e2>band</e2> forced many American jazz and blues singers to seek work in the United Kingdom, which is where Anderson found a receptive audience in 1965."
1 (Cause-Effect(e2,e1))
"<e1>Leakage</e1> and fire caused due to <e2>corrosion</e2> of bypass piping for recirculation gas at a fuel oil desulphurization unit."
1 (Cause-Effect(e2,e1))
"A team of students from Virginia Tech University have created a vehicle that allows vision impaired <e1>drivers</e1> to take control of the <e2>wheel</e2>."
11 (Instrument-Agency(e2,e1))
"BMW's iDrive 4.0 brings in a <e1>horde</e1> of new <e2>features</e2>."
13 (Member-Collection(e2,e1))
"The metal <e1>ball</e1> makes a ding ding ding <e2>noise</e2> when it swings back and hits the metal body of the lamp."
0 (Cause-Effect(e1,e2))
"It consists of an <e1>ensemble</e1> of <e2>ladies</e2> who are highly qualified to play various Arabic musical instruments."
13 (Member-Collection(e2,e1))
"It underscores the need for continued surveillance of nicotine delivery in <e1>products</e1> created by an unregulated <e2>industry</e2>."
16 (Product-Producer(e1,e2))
"Unlike other fish, grunion come out of the water completely to lay their eggs in the wet <e1>sand</e1> of the <e2>beach</e2>."
18 (Other)
"A large <e1>marble</e1> was dropped into the <e2>bowl</e2>."
6 (Entity-Destination(e1,e2))
"Historical view of the <e1>damage</e1> caused by the 1693 Catania <e2>earthquake</e2> and the reconstruction activities."
1 (Cause-Effect(e2,e1))
"AI requested that the perpetrators be prosecuted to the fullest extent of the law, that adequate compensation be provided to the victims and that senior government and police officials offer apologies for the <e1>suffering</e1> caused by the responsible police <e2>officers</e2>."
1 (Cause-Effect(e2,e1))
"The <e1>findings</e1> have been published in a special <e2>section</e2> of the academic journal Archives of Sexual Behavior."
18 (Other)
"An Amtrak <e1>passenger</e1> who alarmed fellow passengers by talking about terrorist threats on a cellphone was pulled from the <e2>train</e2> and is being held in Colorado."
8 (Entity-Origin(e1,e2))
"The <e1>introduction</e1> in the <e2>book</e2> is a summary of what is in the text."
2 (Component-Whole(e1,e2))
"The second <e1>simulation</e1> was started from the uncomplexed x-ray <e2>structure</e2> after insertion of the ligand into the binding site."
8 (Entity-Origin(e1,e2))
"This <e1>user</e1> plays games on a portable <e2>console</e2>."
11 (Instrument-Agency(e2,e1))
"The ambitious Eurasia <e1>exhibition</e1> arose from an <e2>idea</e2> by Achille Bonito Oliva."
8 (Entity-Origin(e1,e2))
"The <e1>driver</e1> of the cement truck cleaned the loading chute on his truck with a truck-mounted water <e2>hose</e2> and began to pull away."
11 (Instrument-Agency(e2,e1))
"The Marshall Plan also provided a way of gaining public acceptance in Europe for the New Deal format that the United States had successfully used before the war to end the <e1>recession</e1> triggered by the 1929 Wall Street <e2>crash</e2>."
1 (Cause-Effect(e2,e1))
"In the corner there are several gate captains and a <e1>legion</e1> of Wu <e2>crossbowmen</e2>."
13 (Member-Collection(e2,e1))
"Once they grow there, the <e1>swelling</e1> and inflammation caused by the <e2>infection</e2> closes off the sac, causing it not to "shed" bacteria, and protecting the bacteria inside from antibiotics and your body's own immune cells."
1 (Cause-Effect(e2,e1))
"Guitars are played acoustically; the <e1>tone</e1> is produced by the <e2>vibration</e2> of the strings which is amplified by the body of the guitar, which acts as a large hollow resonating chamber, or they may rely on an amplifier that can electronically manipulate tone."
1 (Cause-Effect(e2,e1))
End of preview (truncated to 100 rows)

Dataset Card for "sem_eval_2010_task_8"

Dataset Summary

The SemEval-2010 Task 8 focuses on Multi-way classification of semantic relations between pairs of nominals. The task was designed to compare different approaches to semantic relation classification and to provide a standard testbed for future research.

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

default

  • Size of downloaded dataset files: 1.87 MB
  • Size of the generated dataset: 1.35 MB
  • Total amount of disk used: 3.22 MB

An example of 'train' looks as follows.

{
    "relation": 3,
    "sentence": "The system as described above has its greatest application in an arrayed <e1>configuration</e1> of antenna <e2>elements</e2>."
}

Data Fields

The data fields are the same among all splits.

default

  • sentence: a string feature.
  • relation: a classification label, with possible values including Cause-Effect(e1,e2) (0), Cause-Effect(e2,e1) (1), Component-Whole(e1,e2) (2), Component-Whole(e2,e1) (3), Content-Container(e1,e2) (4).

Data Splits

name train test
default 8000 2717

Dataset Creation

Curation Rationale

More Information Needed

Source Data

Initial Data Collection and Normalization

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Who are the source language producers?

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Annotations

Annotation process

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Who are the annotators?

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Personal and Sensitive Information

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Considerations for Using the Data

Social Impact of Dataset

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Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

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Licensing Information

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Citation Information

@inproceedings{hendrickx-etal-2010-semeval,
    title = "{S}em{E}val-2010 Task 8: Multi-Way Classification of Semantic Relations between Pairs of Nominals",
    author = "Hendrickx, Iris  and
      Kim, Su Nam  and
      Kozareva, Zornitsa  and
      Nakov, Preslav  and
      {'O} S{'e}aghdha, Diarmuid  and
      Pad{'o}, Sebastian  and
      Pennacchiotti, Marco  and
      Romano, Lorenza  and
      Szpakowicz, Stan",
    booktitle = "Proceedings of the 5th International Workshop on Semantic Evaluation",
    month = jul,
    year = "2010",
    address = "Uppsala, Sweden",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/S10-1006",
    pages = "33--38",
}

Contributions

Thanks to @JoelNiklaus for adding this dataset.