MMTU-benchmark/MMTU huggingface dataset:
Task: Column-type-annotation (source dataset: SemTab2019)

Your task is to annotate the target entity column in the input table with the DBPedia ontology that can most accurately describe all entities in the column (i.e. use the most fine grained ontology class name that can describe all entities in the column).

No explanation, return the ontology class in JSON format: {"DBpedia ontology class": "<DBpedia ontology class>"}. Please note that DBpedia ontology classes are in the format of "http://dbpedia.org/ontology/<class_name>".

Input Table:
| col0                          | col1                        | col2   | col3                |
|:------------------------------|:----------------------------|:-------|:--------------------|
| Vertebral artery              | Vertebral vein              | a_61   | A07.231.114.839     |
| Superior mesenteric artery    | Superior mesenteric vein    | a_61   | A07.231.114.565.755 |
| Superficial epigastric artery | Superficial epigastric vein | a_61   | A07.231.114.330     |
| Subclavian artery             | Subclavian vein             | a_61   | A07.231.114.839     |
| Splenic artery                | Splenic vein                | a_61   | A07.231.114.814     |
| Scalp                         | Occipital vein              | s_03   | A01.456.810         |
| Renal artery                  | Renal vein                  | a_61   | A07.231.114.745     |
| Rectum                        | Middle rectal veins         | r_05   | A03.556.124.526.767 |
| Posterior cerebral artery     | Cerebral veins              | a_61   | A07.231.114.228.700 |
| Popliteal artery              | Popliteal vein              | a_61   | A07.231.114.681     |
| Ophthalmic artery             | Inferior ophthalmic vein    | a_61   | A07.231.114.622     |
| Navel                         | Umbilical vein              | u_02   | D014472             |
| Lip                           | Inferior labial vein        | l_01   | D008046             |
| Internal thoracic artery      | Internal thoracic vein      | a_61   | A07.231.114.891.525 |
| Internal iliac artery         | Internal iliac vein         | a_61   | A07.231.114.444     |

Target entity column: col0



col_id: 0
label: http://dbpedia.org/ontology/Artery
okay_annotation: http://dbpedia.org/ontology/AnatomicalStructure
csv: v17_489
col_name: col0
case_id: 1189
Task: Column-type-annotation (source dataset: SemTab2019)

Your task is to annotate the target entity column in the input table with the DBPedia ontology that can most accurately describe all entities in the column (i.e. use the most fine grained ontology class name that can describe all entities in the column).

No explanation, return the ontology class in JSON format: {"DBpedia ontology class": "<DBpedia ontology class>"}. Please note that DBpedia ontology classes are in the format of "http://dbpedia.org/ontology/<class_name>".

Input Table:
| col0          | col1       | col2                    | col3         |
|:--------------|:-----------|:------------------------|:-------------|
| R. Gutierrez  | S. Lahbati | Filipino people         | E. Gutierrez |
| M. Wing-Davey | A. Carey   | British nationality law | A. Wing      |
| M. Ek         | H. Klinga  | Sweden                  | A. Ek        |
| J. Rabaeus    | C. Thulin  | Sweden                  | B. Rabaeus   |
| G. Vidal      | H. Austen  | Americans               | E. L. Vidal  |
| E. Fox        | J. Gilley  | British nationality law | E. Fox       |
| C. Caillat    | J. Young   | United States           | K. Caillat   |

Target entity column: col1



col_id: 1
label: http://dbpedia.org/ontology/Person
okay_annotation: nan
csv: v15_534
col_name: col1
case_id: 350
Task: Column-type-annotation (source dataset: SemTab2019)

Your task is to annotate the target entity column in the input table with the DBPedia ontology that can most accurately describe all entities in the column (i.e. use the most fine grained ontology class name that can describe all entities in the column).

No explanation, return the ontology class in JSON format: {"DBpedia ontology class": "<DBpedia ontology class>"}. Please note that DBpedia ontology classes are in the format of "http://dbpedia.org/ontology/<class_name>".

Input Table:
| col0                         |   col1 |   col2 | col3   |
|:-----------------------------|-------:|-------:|:-------|
| Zytek ZRS03                  | 395232 |    447 | DOHC   |
| Volvo B8444S engine          | 232000 |    440 | DOHC   |
| Volkswagen air-cooled engine |  18000 |     68 | I-head |
| Volkswagen G60 engine        | 118000 |    225 | SOHC   |
| Toyota W engine              |  86000 |    275 | I-head |
| Toyota Type A engine         |  19858 |     98 | I-head |
| Toyota GZ engine             | 205939 |    481 | DOHC   |
| Nissan S20 engine            | 120000 |    180 | DOHC   |
| Mercedes-Benz OM654 engine   | 143000 |    400 | DOHC   |
| Mercedes-Benz OM642          | 195000 |    620 | DOHC   |
| Mercedes-Benz M104 engine    | 162000 |    265 | DOHC   |
| IKCO EF Engines              |  61781 |    111 | DOHC   |
| Hyundai Theta engine         | 107000 |    190 | DOHC   |
| Honda Indy V8                | 484719 |    430 | DOHC   |
| General Motors Atlas engine  | 130501 |    250 | DOHC   |
| Ford straight-six engine     |  62640 |    181 | I-head |
| Ford Boss 302 engine         | 216259 |    393 | I-head |
| FCA F160 engine              | 310000 |    550 | DOHC   |
| Daimler V8 engines           | 164054 |    383 | I-head |
| BMW S85                      | 373000 |    520 | DOHC   |
| BMW S65                      | 309000 |    400 | DOHC   |

Target entity column: col0



col_id: 0
label: http://dbpedia.org/ontology/AutomobileEngine
okay_annotation: http://dbpedia.org/ontology/Device http://dbpedia.org/ontology/Engine
csv: v15_565
col_name: col0
case_id: 374
Task: Column-type-annotation (source dataset: SemTab2019)

Your task is to annotate the target entity column in the input table with the DBPedia ontology that can most accurately describe all entities in the column (i.e. use the most fine grained ontology class name that can describe all entities in the column).

No explanation, return the ontology class in JSON format: {"DBpedia ontology class": "<DBpedia ontology class>"}. Please note that DBpedia ontology classes are in the format of "http://dbpedia.org/ontology/<class_name>".

Input Table:
| col0          | col1       | col2      | col3                             |
|:--------------|:-----------|:----------|:---------------------------------|
| D. MacPherson | 1930-11-04 | 4–1–1     | 0–1 (NCAA Division II playoffs)  |
| D. Erickson   | 1947-03-24 | 5–7       | 1–2 (NCAA D-I-AA playoffs)       |
| D. Bailiff    | 1958-05-26 | 3–1       | 2–1 (NCAA D-I-AA playoffs)       |
| D. Maurer     | 1932-03-18 | 1–0       | 9–2 (NCAA D-III playoffs)        |
| D. Mudra      | 1929-01-14 | 3–1       | 4–3 (NCAA D-I-AA playoffs)       |
| D. Hope       | 1959-01-07 | 1–0       | 0–1 (NCAA D-I playoffs)          |
| D. Hawkins    | 1960-11-10 | 2–3       | 4–2 (NAIA playoffs)              |
| C. Schurig    | 1965-03-02 | 2–0       | 1–3 (NCAA D-II playoffs)         |
| C. Carthel    | 1976-08-29 | 1–1       | 0–1 (NCAA D-II playoffs)         |
| C. Klausing   | 1925-04-19 | 0–1       | 2–4 (NCAA D-III playoffs)        |
| C. Broyles    | 1947-02-05 | 1&ndash;0 | 19&ndash;14 (NCAA D-II playoffs) |
| C. Thomsen    | 1970-0-0   | 1–0       | 2–5 (1 win vacated)              |

Target entity column: col0



col_id: 0
label: http://dbpedia.org/ontology/CollegeCoach
okay_annotation: http://dbpedia.org/ontology/Coach http://dbpedia.org/ontology/Person
csv: v16_50
col_name: col0
case_id: 513
Task: Column-type-annotation (source dataset: SemTab2019)

Your task is to annotate the target entity column in the input table with the DBPedia ontology that can most accurately describe all entities in the column (i.e. use the most fine grained ontology class name that can describe all entities in the column).

No explanation, return the ontology class in JSON format: {"DBpedia ontology class": "<DBpedia ontology class>"}. Please note that DBpedia ontology classes are in the format of "http://dbpedia.org/ontology/<class_name>".

Input Table:
| col0          | col1       | col2   | col3                         |
|:--------------|:-----------|:-------|:-----------------------------|
| C. Creighton  | 1969-02-07 | 1–0    | 0–2 (NAIA playoffs)          |
| C. Ault       | 1946-11-08 | 2–8    | 9–7 (NCAA D-I-AA playoffs)   |
| B. Kelly      | 1961-10-25 | 5–4    | 11–4 (NCAA D-II playoffs)    |
| B. Johnson    | 1951-02-08 | 1–0    | 3–3 (NCAA D-I-AA playoffs)   |
| B. Pruett     | 1943-06-20 | 5–2    | 4–0 (NCAA D-I-AA playoffs)   |
| B. Ford       | 1937-09-11 | 2–1    | 0–1 (NCAA D-I FCS playoffs)  |
| B. Atterberry | 1975-02-21 | 0–1    | 0–2 (NCAA D-II playoffs)     |
| B. Cotton     | 1956-09-30 | 0–1    | 0–1                          |
| A. Molde      | 1943-11-15 | 0–1    | 1–2 (NCAA Div I-AA playoffs) |

Target entity column: col0



col_id: 0
label: http://dbpedia.org/ontology/CollegeCoach
okay_annotation: http://dbpedia.org/ontology/Coach http://dbpedia.org/ontology/Person
csv: v16_51
col_name: col0
case_id: 514
Task: Column-type-annotation (source dataset: SemTab2019)

Your task is to annotate the target entity column in the input table with the DBPedia ontology that can most accurately describe all entities in the column (i.e. use the most fine grained ontology class name that can describe all entities in the column).

No explanation, return the ontology class in JSON format: {"DBpedia ontology class": "<DBpedia ontology class>"}. Please note that DBpedia ontology classes are in the format of "http://dbpedia.org/ontology/<class_name>".

Input Table:
| col0       | col1                                          | col2                      | col3            |
|:-----------|:----------------------------------------------|:--------------------------|:----------------|
| N. Scott   | A. Provosty                                   | J. Scott                  | Louisiana       |
| J. Verney  | George Verney, 12th Baron Willoughby de Broke | Baron Willoughby de Broke | Kent            |
| J. Iqbal   | Y. Salahuddin                                 | W. Iqbal                  | Punjab Province |
| H. C. Drew | H. D. Jr.                                     | R. Harmon Drew, Sr.       | Louisiana       |
| B. Laskin  | S. Laskin                                     | J. I. Laskin              | Ontario         |
| B. O'Keefe | J. O'Keefe                                    | A. O'Keefe                | New South Wales |

Target entity column: col0



col_id: 0
label: http://dbpedia.org/ontology/Judge
okay_annotation: http://dbpedia.org/ontology/Person
csv: v16_876
col_name: col0
case_id: 983
Task: Column-type-annotation (source dataset: SemTab2019)

Your task is to annotate the target entity column in the input table with the DBPedia ontology that can most accurately describe all entities in the column (i.e. use the most fine grained ontology class name that can describe all entities in the column).

No explanation, return the ontology class in JSON format: {"DBpedia ontology class": "<DBpedia ontology class>"}. Please note that DBpedia ontology classes are in the format of "http://dbpedia.org/ontology/<class_name>".

Input Table:
| col0                                     | col1          |   col2 | col3                                |     col4 |
|:-----------------------------------------|:--------------|-------:|:------------------------------------|---------:|
| Ventromedial nucleus of the hypothalamus | Hypothalamus  |    381 | A08.186.211.730.385.357.352.953     | 12584102 |
| Subthalamic nucleus                      | Basal ganglia |    418 | A08.186.211.730.385.800.800         | 14166739 |
| Pulvinar nuclei                          | Thalamus      |    311 | A08.186.211.730.385.826.701.485.600 | 12680162 |
| Nucleus accumbens                        | Basal ganglia |    259 | A08.186.211.730.885.105.683         | 12580142 |
| Medulla oblongata                        | Brain stem    |    695 | A08.186.211.132.810.406             | 12519731 |
| Brainstem                                | Brain         |    218 | A08.186.211.132                     | 12195821 |
| Basal ganglia                            | Cerebrum      |    206 | A08.186.211.730.885.105             | 12580456 |
| Arcuate nucleus                          | Hypothalamus  |    378 | A08.186.211.730.385.357.352.081     | 12580380 |
| Arachnoid mater                          | Meninges      |    561 | A08.186.566.166                     | 12149123 |

Target entity column: col1



col_id: 1
label: http://dbpedia.org/ontology/Brain
okay_annotation: http://dbpedia.org/ontology/AnatomicalStructure
csv: v16_716
col_name: col1
case_id: 950
Task: Column-type-annotation (source dataset: SemTab2019)

Your task is to annotate the target entity column in the input table with the DBPedia ontology that can most accurately describe all entities in the column (i.e. use the most fine grained ontology class name that can describe all entities in the column).

No explanation, return the ontology class in JSON format: {"DBpedia ontology class": "<DBpedia ontology class>"}. Please note that DBpedia ontology classes are in the format of "http://dbpedia.org/ontology/<class_name>".

Input Table:
| col0          | col1            | col2           | col3                   | col4          | col5          |
|:--------------|:----------------|:---------------|:-----------------------|:--------------|:--------------|
| Y. Kavaguti   | N. Velikov      | P. Tchernyshev | Funabashi, Chiba       | I. Bobrin     | A. Markuntsov |
| Y. Xiaoyu     | L. Bo           | D. Wilson      | Beijing                | M. Zueva      | J. Yang       |
| T. Zahorski   | O. Schoenfelder | A. Zhulin      | London                 | R. Haguenauer | A. Miart      |
| T. Volosozhar | I. Steuer       | N. Morozov     | Dnipropetrovsk         | A. Zhulin     | S. Morozov    |
| P. Gilles     | C. Dean         | P. Poirier     | Rockford, Illinois     | C. Dean       | Z. Donohue    |
| P. Carron     | R. Haguenauer   | L. Jones       | Villefranche-sur-Saône | M. Dubreuil   | M. Jost       |
| O. Japaridze  | N. Morozov      | E. Platov      | Tbilisi                | N. Morozov    | I. Tobias     |
| O. Hotárek    | J. Dungjen      | M. Scali       | Brno                   | A. Krylova    | V. Havlíčková |
| N. Katsalapov | A. Zhulin       | N. Morozov     | Moscow                 | A. Zhulin     | E. Ilinykh    |
| N. Orford     | M. Wing         | J. Razgulajevs | Calgary                | M. Wing       | T. Williams   |
| N. Takahashi  | J. Dungjen      | N. Morozov     | Chiba, Chiba           | M. Zueva      | M. Tran       |
| M. Trankov    | N. Velikov      | N. Morozov     | Perm                   | A. Zhulin     | A. Ulanov     |
| M. Mukhortova | A. Dmitriev     | A. Matveev     | St. Petersburg, Russia | T. Druchinina | P. Lebedev    |

Target entity column: col4



col_id: 4
label: http://dbpedia.org/ontology/FigureSkater
okay_annotation: http://dbpedia.org/ontology/Person http://dbpedia.org/ontology/Athlete http://dbpedia.org/ontology/WinterSportPlayer
csv: v17_198
col_name: col4
case_id: 1089
Task: Column-type-annotation (source dataset: SemTab2019)

Your task is to annotate the target entity column in the input table with the DBPedia ontology that can most accurately describe all entities in the column (i.e. use the most fine grained ontology class name that can describe all entities in the column).

No explanation, return the ontology class in JSON format: {"DBpedia ontology class": "<DBpedia ontology class>"}. Please note that DBpedia ontology classes are in the format of "http://dbpedia.org/ontology/<class_name>".

Input Table:
| col0                          | col1   |   col2 |   col3 | col4      |   col5 |
|:------------------------------|:-------|-------:|-------:|:----------|-------:|
| Asparagine synthetase         | ASNS   | 108370 |    440 | 6.3.5.4   |    753 |
| Angiopoietin receptor         | TEK    | 600221 |   7010 | 2.7.1.112 |  11724 |
| Alpha-N-acetylglucosaminidase | NAGLU  | 609701 |   4669 | 3.2.1.50  |   7632 |
| Alanine transaminase          | GPT    | 138200 |   2875 | 2.6.1.2   |   4552 |
| Acyltransferase like 2        | AYTL2  | 610472 |  79888 | 2.3.1.23  |  25718 |
| ATP2A2                        | ATP2A2 | 108740 |    488 | 3.6.3.8   |    812 |
| 6-phosphogluconolactonase     | PGLS   | 604951 |  25796 | 3.1.1.31  |   8903 |
| 3-Hydroxyacyl ACP dehydrase   | ECHD   | 607037 |   1962 | 4.2.1.17  |   3247 |
| 2,4 Dienoyl-CoA reductase     | DECR   | 222745 |   1666 | 1.3.1.34  |   2753 |

Target entity column: col0



col_id: 0
label: http://dbpedia.org/ontology/Protein
okay_annotation: http://dbpedia.org/ontology/Biomolecule
csv: v17_620
col_name: col0
case_id: 1229
Task: Column-type-annotation (source dataset: SemTab2019)

Your task is to annotate the target entity column in the input table with the DBPedia ontology that can most accurately describe all entities in the column (i.e. use the most fine grained ontology class name that can describe all entities in the column).

No explanation, return the ontology class in JSON format: {"DBpedia ontology class": "<DBpedia ontology class>"}. Please note that DBpedia ontology classes are in the format of "http://dbpedia.org/ontology/<class_name>".

Input Table:
| col0                           | col1          | col2      |   col3 |
|:-------------------------------|:--------------|:----------|-------:|
| Wired                          | L. Rossetto   | 1059-1028 | 851823 |
| Vibe                           | A. Light      | 1070-4701 | 301408 |
| Uncut                          | A. Jones      | 1368-0722 |  47890 |
| The State of Australia's Birds | P. Olsen      | 1036-7810 |   8000 |
| The Railway Magazine           | G. A. Nokes   | 0033-8923 |   2015 |
| The Nation                     | N. Thomas     | 0027-8378 | 103478 |
| The Hockey News                | B. McKenzie   | 0018-3016 | 100058 |
| The Classic Motor Cycle        | B. Currie     | 0263-0850 |  78993 |
| Teraz Rock                     | T. Rock       | 1730-394X |  40000 |
| Sunt Förnuft                   | S. Nordin     | 0039-5455 |  43500 |
| Shonen Jump                    | J. Thompson   | 1545-7818 | 215000 |
| Shojo Beat                     | M. Weidenbaum | 1932-1600 |  38000 |
| Shift                          | E. Solomon    | 1188-973X | 150000 |

Target entity column: col1



col_id: 1
label: http://dbpedia.org/ontology/Person
okay_annotation: nan
csv: v17_950
col_name: col1
case_id: 1356
Task: Column-type-annotation (source dataset: SemTab2019)

Your task is to annotate the target entity column in the input table with the DBPedia ontology that can most accurately describe all entities in the column (i.e. use the most fine grained ontology class name that can describe all entities in the column).

No explanation, return the ontology class in JSON format: {"DBpedia ontology class": "<DBpedia ontology class>"}. Please note that DBpedia ontology classes are in the format of "http://dbpedia.org/ontology/<class_name>".

Input Table:
| col0                      | col1                     | col2          | col3          | col4                     |
|:--------------------------|:-------------------------|:--------------|:--------------|:-------------------------|
| 1930 Monza Grand Prix     | Maserati in motorsport   | E. Maserati   | Italy         | Maserati in motorsport   |
| 1925 Italian Grand Prix   | Alfa Romeo in motorsport | M. Costantini | Italy         | Alfa Romeo in motorsport |
| 1925 French Grand Prix    | Delage                   | G. Masetti    | France        | Delage                   |
| 1924 Italian Grand Prix   | Alfa Romeo in motorsport | G. Campari    | Italy         | Alfa Romeo in motorsport |
| 1923 Italian Grand Prix   | Fiat                     | J. A. Murphy  | Italy         | Fiat                     |
| 1922 Italian Grand Prix   | Fiat                     | P. d. Vizcaya | Italy         | Fiat                     |
| 1913 French Grand Prix    | Peugot                   | J. Chassagne  | France        | Peugot                   |
| 1912 American Grand Prize | Fiat                     | G. Andersen   | United States | Benz Söhne               |
| 1911 American Grand Prize | Fiat                     | R. DePalma    | United States | Benz Söhne               |
| 1910 American Grand Prize | Mercedes-Benz            | B. Burman     | United States | Mercedes-Benz            |
| 1905 Gordon Bennett Cup   | Brasier                  | A. Cagno      | France        | Fiat                     |

Target entity column: col4



col_id: 4
label: http://dbpedia.org/ontology/Company
okay_annotation: http://dbpedia.org/ontology/Organisation
csv: v17_276
col_name: col4
case_id: 1108
Task: Column-type-annotation (source dataset: SemTab2019)

Your task is to annotate the target entity column in the input table with the DBPedia ontology that can most accurately describe all entities in the column (i.e. use the most fine grained ontology class name that can describe all entities in the column).

No explanation, return the ontology class in JSON format: {"DBpedia ontology class": "<DBpedia ontology class>"}. Please note that DBpedia ontology classes are in the format of "http://dbpedia.org/ontology/<class_name>".

Input Table:
| col0                                | col1          | col2               | col3                        |
|:------------------------------------|:--------------|:-------------------|:----------------------------|
| W. Queen                            | Pawn          | Looking-Glass Land | R. Queen                    |
| Tarzan                              | Korak         | English language   | Tarzan and the Tarzan Twins |
| S. White                            | E. Swan       | Bavaria            | E. Queen                    |
| Selene                              | Underworld    | Hungarian people   | Underworld                  |
| R. Grant                            | N. Grant      | United States      | B. Henrickson               |
| R. Forman                           | E. Forman     | United States      | Fez                         |
| N. Powers                           | D. Evil       | United Kingdom     | S. Evil                     |
| N. Grant                            | B. Henrickson | United States      | R. Grant                    |
| M. Anagnostou                       | Erotas        | Greece             | Erotas                      |
| M. Ravenwood                        | M. Williams   | United States      | A. Ravenwood                |
| L. Griffin                          | S. Griffin    | United States      | B. Pewterschmidt            |
| List of Disney's Aladdin characters | Descendants   | Arabian            | P. Jasmine                  |
| L. Munster                          | E. Munster    | United States      | Grandpa                     |
| L. Sternin                          | F. Crane      | United States      | M. Crane                    |
| L. d. Lioncourt                     | Claudia       | French people      | G. d. Lioncourt             |
| Kyrano                              | T. Kyrano     | Malaysia           | T. Hood                     |
| K. Forman                           | E. Forman     | United States      | Fez                         |
| J. Valjean                          | Cosette       | France             | M. Pontmercy                |
| J. Porter                           | Korak         | England            | Meriem, wife of Korak       |

Target entity column: col3



col_id: 3
label: http://dbpedia.org/ontology/FictionalCharacter
okay_annotation: http://dbpedia.org/ontology/Person
csv: v17_192
col_name: col3
case_id: 1075
Task: Column-type-annotation (source dataset: SemTab2019)

Your task is to annotate the target entity column in the input table with the DBPedia ontology that can most accurately describe all entities in the column (i.e. use the most fine grained ontology class name that can describe all entities in the column).

No explanation, return the ontology class in JSON format: {"DBpedia ontology class": "<DBpedia ontology class>"}. Please note that DBpedia ontology classes are in the format of "http://dbpedia.org/ontology/<class_name>".

Input Table:
| col0                | col1          | col2         |   col3 |
|:--------------------|:--------------|:-------------|-------:|
| Ungli               | H. Chaturvedi | D. Bhatia    |   6840 |
| Unforgiven          | J. N. Green   | J. Cox       |   7860 |
| Unfinished Business | O. Stapleton  | M. Tronick   |   5460 |
| Unfinished Business | S. Okazaki    | S. Okazaki   |   3600 |
| Unfaithfully Yours  | D. M. Walsh   | S. Kahn      |   5760 |
| Unfaithful          | P. Biziou     | A. V. Coates |   7440 |
| Unfair Competition  | F. D. Giacomo | R. Crociani  |   6600 |
| Unexpected Conflict | E. Serafin    | J. Palleja   |   5580 |
| Uneasy Terms        | E. Palmer     | M. Kimick    |   5460 |
| Unearthly Stranger  | R. Wyer       | T. Priestley |   4680 |

Target entity column: col1



col_id: 1
label: http://dbpedia.org/ontology/Person
okay_annotation: nan
csv: v16_272
col_name: col1
case_id: 654
Task: Column-type-annotation (source dataset: SemTab2019)

Your task is to annotate the target entity column in the input table with the DBPedia ontology that can most accurately describe all entities in the column (i.e. use the most fine grained ontology class name that can describe all entities in the column).

No explanation, return the ontology class in JSON format: {"DBpedia ontology class": "<DBpedia ontology class>"}. Please note that DBpedia ontology classes are in the format of "http://dbpedia.org/ontology/<class_name>".

Input Table:
| col0          | col1       | col2                    | col3         |
|:--------------|:-----------|:------------------------|:-------------|
| R. Gutierrez  | S. Lahbati | Filipino people         | E. Gutierrez |
| M. Wing-Davey | A. Carey   | British nationality law | A. Wing      |
| M. Ek         | H. Klinga  | Sweden                  | A. Ek        |
| J. Rabaeus    | C. Thulin  | Sweden                  | B. Rabaeus   |
| G. Vidal      | H. Austen  | Americans               | E. L. Vidal  |
| E. Fox        | J. Gilley  | British nationality law | E. Fox       |
| C. Caillat    | J. Young   | United States           | K. Caillat   |

Target entity column: col2



col_id: 2
label: http://dbpedia.org/ontology/Country
okay_annotation: http://dbpedia.org/ontology/AdministrativeRegion http://dbpedia.org/ontology/Place http://dbpedia.org/ontology/PopulatedPlace http://dbpedia.org/ontology/Region http://dbpedia.org/ontology/Location
csv: v15_534
col_name: col2
case_id: 351
Task: Column-type-annotation (source dataset: SemTab2019)

Your task is to annotate the target entity column in the input table with the DBPedia ontology that can most accurately describe all entities in the column (i.e. use the most fine grained ontology class name that can describe all entities in the column).

No explanation, return the ontology class in JSON format: {"DBpedia ontology class": "<DBpedia ontology class>"}. Please note that DBpedia ontology classes are in the format of "http://dbpedia.org/ontology/<class_name>".

Input Table:
| col0           | col1                           | col2           | col3       |
|:---------------|:-------------------------------|:---------------|:-----------|
| F. Emelianenko | Belgorod Oblast                | E. Hoost       | 1976-09-28 |
| Esui           | Japan                          | M. Yoshida     | 1985-05-09 |
| E. Barboza     | United States                  | R. Almeida     | 1986-01-21 |
| C. Marcello    | Brazil                         | R. Gracie      | 1977-12-3  |
| C. Schneider   | California                     | E. Paulson     | 1982-03-12 |
| C. Dolman      | Amsterdam                      | J. Bluming     | 1945-02-17 |
| C. Brenneman   | East Stroudsburg, Pennsylvania | M. Constantino | 1981-2-9   |
| C. Condit      | New Mexico                     | G. Jackson     | 1984-04-26 |
| B. Adegbuyi    | Bucharest                      | H. coach       | 1985-01-24 |
| B. Rutten      | Los Angeles, California        | M. Funaki      | 1965-02-24 |
| B. Nansen      | Auckland, New Zealand          | J. Conway      | 1987-01-11 |
| A. Hamasaki    | Japan                          | M. Fujii       | 1982-03-31 |
| A. Gomez       | Tinley Park, Illinois          | M. Torres      | 1982-1-1   |
| A. Koreshkov   | Russia                         | A. Shlemenko   | 1990-08-23 |
| A. Silva       | Los Angeles, California        | A. R. Nogueira | 1975-04-14 |
| A. Lloveras    | Barcelona                      | G. Gonzaga     | 1982-09-04 |

Target entity column: col1



col_id: 1
label: http://dbpedia.org/ontology/City
okay_annotation: http://dbpedia.org/ontology/AdministrativeRegion http://dbpedia.org/ontology/Settlement http://dbpedia.org/ontology/Place http://dbpedia.org/ontology/PopulatedPlace http://dbpedia.org/ontology/Region http://dbpedia.org/ontology/Location
csv: v16_953
col_name: col1
case_id: 1000
Task: Column-type-annotation (source dataset: SemTab2019)

Your task is to annotate the target entity column in the input table with the DBPedia ontology that can most accurately describe all entities in the column (i.e. use the most fine grained ontology class name that can describe all entities in the column).

No explanation, return the ontology class in JSON format: {"DBpedia ontology class": "<DBpedia ontology class>"}. Please note that DBpedia ontology classes are in the format of "http://dbpedia.org/ontology/<class_name>".

Input Table:
| col0                        | col1                    | col2         | col3       | col4       |
|:----------------------------|:------------------------|:-------------|:-----------|:-----------|
| Kamen Rider W               | Kamen Rider Decade      | K. Nakagawa  | F. Tachiki | 2010-08-29 |
| Kamen Rider V3              | Kamen Rider             | S. Kikuchi   | S. Nakae   | 1974-02-09 |
| Kamen Rider Stronger        | Kamen Rider Amazon      | S. Kikuchi   | S. Nakae   | 1975-12-27 |
| Kamen Rider OOO             | Kamen Rider W           | K. Nakagawa  | J. Nakata  | 2011-08-28 |
| Kamen Rider Kiva            | Kamen Rider Den-O       | T. Saito     | A. Ishida  | 2009-01-18 |
| Kamen Rider Gaim            | Kamen Rider Wizard      | K. Yamashita | H. Ōtsuka  | 2014-09-28 |
| Kamen Rider Fourze          | Kamen Rider OOO         | S. Naruse    | N. Hiyama  | 2012-08-26 |
| Kamen Rider Drive           | Kamen Rider Gaim        | K. Nakagawa  | C. Peppler | 2015-09-27 |
| Kamen Rider Amazon          | Kamen Rider X           | S. Kikuchi   | G. Naya    | 1975-03-29 |
| Kaizoku Sentai Gokaiger     | Tensou Sentai Goseiger  | K. Yamashita | T. Seki    | 2012-02-19 |
| Ja'mie: Private School Girl | Angry Boys              | C. Lilley    | C. Lilley  | 2013-11-27 |
| Hyakujuu Sentai Gaoranger   | Mirai Sentai Timeranger | K. Nakagawa  | H. Masuoka | 2002-02-10 |

Target entity column: col3



col_id: 3
label: http://dbpedia.org/ontology/Person
okay_annotation: nan
csv: v17_230
col_name: col3
case_id: 1094
Task: Column-type-annotation (source dataset: SemTab2019)

Your task is to annotate the target entity column in the input table with the DBPedia ontology that can most accurately describe all entities in the column (i.e. use the most fine grained ontology class name that can describe all entities in the column).

No explanation, return the ontology class in JSON format: {"DBpedia ontology class": "<DBpedia ontology class>"}. Please note that DBpedia ontology classes are in the format of "http://dbpedia.org/ontology/<class_name>".

Input Table:
| col0          | col1                           | col2       | col3       |
|:--------------|:-------------------------------|:-----------|:-----------|
| B. Rose       | Sedgewick, Alberta             | 1987-10-06 | 1904-04-11 |
| B. Tetley     | Thunder Bay, Ontario           | 2003-06-09 | 1933-07-11 |
| B. Grant      | Manitoba                       | 1942-04-16 | 1882-06-16 |
| B. Naimark    | Halfmoon Bay, British Columbia | 2004-12-03 | 1932-07-01 |
| A. Pollon     | Salmon Arm, British Columbia   | 2009-03-28 | 1914-08-20 |
| A. Kleinmeyer | Athabasca, Alberta             | 2000-12-23 | 1914-0-0   |
| A. McWilliams | Winnipeg, Manitoba             | 1995-03-23 | 1916-10-16 |
| A. Welsh      | Winnipeg, Manitoba             | 1971-01-04 | 1907-10-12 |
| A. Langlois   | Manitoba                       | 2005-01-30 | 1915-08-04 |
| A. Gowanlock  | Dauphin, Manitoba              | 1988-09-27 | 1900-12-14 |

Target entity column: col0



col_id: 0
label: http://dbpedia.org/ontology/Curler
okay_annotation: http://dbpedia.org/ontology/Person http://dbpedia.org/ontology/Athlete http://dbpedia.org/ontology/WinterSportPlayer
csv: v15_90
col_name: col0
case_id: 43
Task: Column-type-annotation (source dataset: SemTab2019)

Your task is to annotate the target entity column in the input table with the DBPedia ontology that can most accurately describe all entities in the column (i.e. use the most fine grained ontology class name that can describe all entities in the column).

No explanation, return the ontology class in JSON format: {"DBpedia ontology class": "<DBpedia ontology class>"}. Please note that DBpedia ontology classes are in the format of "http://dbpedia.org/ontology/<class_name>".

Input Table:
| col0            | col1                     | col2                      | col3       |
|:----------------|:-------------------------|:--------------------------|:-----------|
| W. Lloyd        | M. Dawson                | New York City             | 1994-8-24  |
| S. Reid         | J. Jareau                | Las Vegas                 | 1981-10-0  |
| P. J. Fry       | The Luck of the Fryrish  | Brooklyn                  | 1974-8-9   |
| L. P. Wimsey    | C. Parker                | Hampshire                 | 1890-0-0   |
| L. d. Lioncourt | G. d. Lioncourt          | History of Auvergne       | 1760-11-7  |
| K. Bauer        | J. Bauer                 | Santa Monica, California  | 1987-1-1   |
| J. Bartlet      | J. Bartlett              | Manchester, New Hampshire | 1942-0-0   |
| J. Clark        | D. Chavez                | Indianapolis              | 1944-1-1   |
| J. Adams        | L. Adams                 | Tufnell Park              | 1991-10-27 |
| J. Shephard     | C. Shephard              | Los Angeles               | 1969-12-3  |
| J. Bauer        | G. Bauer                 | Santa Monica, California  | 1966-2-18  |
| H. Mills        | Wicked Witch of the West | Phoenix, Arizona          | 2001-0-0   |
| H. T. Dog       | D. T. Dog                | Wigan                     | 2005-10-27 |
| G. V. Pelt      | A. football              | Iowa                      | 1983-4-4   |
| Gorgythion      | Antiphus                 | Troy                      | 12         |
| E. Cullen       | C. Cullen                | Chicago                   | 1901-0-0   |
| D. Palmer       | W. Palmer                | Philadelphia              | 1953-0-0   |
| C. Littleton    | C. Shephard              | Sydney                    | 1982-10-27 |

Target entity column: col2



col_id: 2
label: http://dbpedia.org/ontology/City
okay_annotation: http://dbpedia.org/ontology/AdministrativeRegion http://dbpedia.org/ontology/Settlement http://dbpedia.org/ontology/Place http://dbpedia.org/ontology/PopulatedPlace http://dbpedia.org/ontology/Region http://dbpedia.org/ontology/Location
csv: v15_151
col_name: col2
case_id: 56
Task: Column-type-annotation (source dataset: SemTab2019)

Your task is to annotate the target entity column in the input table with the DBPedia ontology that can most accurately describe all entities in the column (i.e. use the most fine grained ontology class name that can describe all entities in the column).

No explanation, return the ontology class in JSON format: {"DBpedia ontology class": "<DBpedia ontology class>"}. Please note that DBpedia ontology classes are in the format of "http://dbpedia.org/ontology/<class_name>".

Input Table:
| col0                          | col1                      | col2               | col3                     |
|:------------------------------|:--------------------------|:-------------------|:-------------------------|
| 1929 Monaco Grand Prix        | Bugatti                   | W. Grover-Williams | Bugatti                  |
| 1929 German Grand Prix        | Bugatti                   | L. Chiron          | Bugatti                  |
| 1928 Italian Grand Prix       | Talbot                    | L. Arcangeli       | Alfa Romeo               |
| 1927 Italian Grand Prix       | Delage                    | R. Benoist         | Officine Meccaniche      |
| 1926 San Sebastián Grand Prix | Delage                    | L. Wagner          | Delage                   |
| 1926 Italian Grand Prix       | Bugatti                   | M. Costantini      | Bugatti                  |
| 1926 French Grand Prix        | Bugatti                   | J. Goux            | Bugatti                  |
| 1926 British Grand Prix       | Talbot                    | H. Segrave         | Bugatti                  |
| 1925 Italian Grand Prix       | Duesenberg                | P. Kreis           | Alfa Romeo in motorsport |
| 1925 French Grand Prix        | Sunbeam Motor Car Company | A. Divo            | Delage                   |
| 1925 Belgian Grand Prix       | Alfa Romeo in motorsport  | A. Ascari          | Alfa Romeo in motorsport |
| 1924 Italian Grand Prix       | Alfa Romeo in motorsport  | A. Ascari          | Alfa Romeo in motorsport |
| 1924 French Grand Prix        | Sunbeam Motor Car Company | H. Segrave         | Delage                   |
| 1923 Italian Grand Prix       | Fiat                      | P. Bordino         | Fiat                     |

Target entity column: col0



col_id: 0
label: http://dbpedia.org/ontology/GrandPrix
okay_annotation: http://dbpedia.org/ontology/SportsEvent http://dbpedia.org/ontology/Event http://dbpedia.org/ontology/SocietalEvent
csv: v16_347
col_name: col0
case_id: 682
Task: Column-type-annotation (source dataset: SemTab2019)

Your task is to annotate the target entity column in the input table with the DBPedia ontology that can most accurately describe all entities in the column (i.e. use the most fine grained ontology class name that can describe all entities in the column).

No explanation, return the ontology class in JSON format: {"DBpedia ontology class": "<DBpedia ontology class>"}. Please note that DBpedia ontology classes are in the format of "http://dbpedia.org/ontology/<class_name>".

Input Table:
| col0             |   col1 | col2       | col3       |
|:-----------------|-------:|:-----------|:-----------|
| USS Towaliga     |      5 | 1944-09-29 | 1944-12-14 |
| USS Tourmaline   |      3 | 1930-01-09 | 1941-06-07 |
| USS Toucey       |      2 | 1919-04-26 | 1919-12-09 |
| USS Toucan       |      3 | 1944-02-16 | 1944-11-25 |
| USS Tortuga      |      6 | 1987-03-23 | 1990-11-17 |
| USS Torsk        |      5 | 1944-06-07 | 1944-12-16 |
| USS Torrance     |      7 | 1944-04-01 | 1944-11-18 |
| USS Toro         |      5 | 1944-05-27 | 1944-12-08 |
| USS Torchwood    |      3 | 1943-06-02 | 1944-05-12 |
| USS Topeka       |      7 | 1943-04-21 | 1944-12-23 |
| USS Tonawanda    |      3 | 1944-09-12 | 1945-05-09 |
| USS Tombigbee    |      4 | 1942-10-23 | 1944-07-13 |
| USS Tolman       |      5 | 1944-04-10 | 1944-10-27 |
| USS Tollberg     |      3 | 1943-12-30 | 1945-01-31 |
| USS Tolland      |      7 | 1944-04-22 | 1944-09-04 |
| USS Toledo       |      6 | 1943-09-13 | 1946-10-27 |
| USS Token        |      3 | 1941-07-21 | 1942-12-31 |
| USS Todd         |      7 | 1944-08-10 | 1944-11-30 |
| USS Tisdale      |      3 | 1943-01-23 | 1943-10-11 |
| USS Tiru         |      5 | 1944-04-17 | 1948-09-01 |
| USS Tirante      |      5 | 1944-04-28 | 1944-11-06 |
| USS Tippecanoe   |      8 | 1919-10-01 | 1940-03-06 |
| USS Tioga County |      5 | 1952-06-16 | 1953-06-20 |
| USS Tinsman      |      2 | 1943-12-21 | 1944-06-26 |
| USS Tinosa       |      8 | 1959-11-24 | 1964-10-17 |
| USS Tinosa       |      5 | 1942-02-21 | 1943-01-15 |
| USS Tingey       |      1 | 1899-03-29 | 1904-01-07 |
| USS Tingey       |      5 | 1942-10-22 | 1943-11-25 |
| USS Tingey       |      3 | 1918-08-08 | 1919-07-25 |
| USS Timbalier    |      3 | 1942-11-09 | 1946-05-24 |

Target entity column: col0



col_id: 0
label: http://dbpedia.org/ontology/Ship
okay_annotation: http://dbpedia.org/ontology/MeanOfTransportation http://dbpedia.org/ontology/Locomotive http://dbpedia.org/ontology/Aircraft http://dbpedia.org/ontology/Automobile http://dbpedia.org/ontology/MilitaryVehicle
csv: v18_918
col_name: col0
case_id: 1712
Task: Column-type-annotation (source dataset: SemTab2019)

Your task is to annotate the target entity column in the input table with the DBPedia ontology that can most accurately describe all entities in the column (i.e. use the most fine grained ontology class name that can describe all entities in the column).

No explanation, return the ontology class in JSON format: {"DBpedia ontology class": "<DBpedia ontology class>"}. Please note that DBpedia ontology classes are in the format of "http://dbpedia.org/ontology/<class_name>".

Input Table:
| col0         | col1                             | col2        | col3                           |
|:-------------|:---------------------------------|:------------|:-------------------------------|
| W. Foulke    | Chelsea F.C.                     | Shropshire  | Sheffield                      |
| T. Revill    | Stoke City F.C.                  | England     | England                        |
| S. McMillan  | Chelsea F.C.                     | Leicester   | Ashbourne, Derbyshire          |
| N. Cantwell  | Manchester United F.C.           | Cork        | Peterborough                   |
| K. Hough     | Australia national football team | Australia   | Australia                      |
| G. Brann     | England national football team   | Eastbourne  | England national football team |
| F. Gardner   | Birmingham City F.C.             | Coventry    | Coventry                       |
| F. Guttridge | Nottingham Forest F.C.           | Nottingham  | Nottingham                     |
| E. Burgin    | Sheffield United F.C.            | Pitsmoor    | Sheffield                      |
| A. Holt      | Southampton F.C.                 | Southampton | Southampton                    |

Target entity column: col1



col_id: 1
label: http://dbpedia.org/ontology/SoccerClub
okay_annotation: http://dbpedia.org/ontology/SportsTeam http://dbpedia.org/ontology/Organisation
csv: v16_125
col_name: col1
case_id: 555
Task: Column-type-annotation (source dataset: SemTab2019)

Your task is to annotate the target entity column in the input table with the DBPedia ontology that can most accurately describe all entities in the column (i.e. use the most fine grained ontology class name that can describe all entities in the column).

No explanation, return the ontology class in JSON format: {"DBpedia ontology class": "<DBpedia ontology class>"}. Please note that DBpedia ontology classes are in the format of "http://dbpedia.org/ontology/<class_name>".

Input Table:
| col0                      | col1                     | col2          | col3          | col4                     |
|:--------------------------|:-------------------------|:--------------|:--------------|:-------------------------|
| 1930 Monza Grand Prix     | Maserati in motorsport   | E. Maserati   | Italy         | Maserati in motorsport   |
| 1925 Italian Grand Prix   | Alfa Romeo in motorsport | M. Costantini | Italy         | Alfa Romeo in motorsport |
| 1925 French Grand Prix    | Delage                   | G. Masetti    | France        | Delage                   |
| 1924 Italian Grand Prix   | Alfa Romeo in motorsport | G. Campari    | Italy         | Alfa Romeo in motorsport |
| 1923 Italian Grand Prix   | Fiat                     | J. A. Murphy  | Italy         | Fiat                     |
| 1922 Italian Grand Prix   | Fiat                     | P. d. Vizcaya | Italy         | Fiat                     |
| 1913 French Grand Prix    | Peugot                   | J. Chassagne  | France        | Peugot                   |
| 1912 American Grand Prize | Fiat                     | G. Andersen   | United States | Benz Söhne               |
| 1911 American Grand Prize | Fiat                     | R. DePalma    | United States | Benz Söhne               |
| 1910 American Grand Prize | Mercedes-Benz            | B. Burman     | United States | Mercedes-Benz            |
| 1905 Gordon Bennett Cup   | Brasier                  | A. Cagno      | France        | Fiat                     |

Target entity column: col3



col_id: 3
label: http://dbpedia.org/ontology/Country
okay_annotation: http://dbpedia.org/ontology/AdministrativeRegion http://dbpedia.org/ontology/Place http://dbpedia.org/ontology/PopulatedPlace http://dbpedia.org/ontology/Region http://dbpedia.org/ontology/Location
csv: v17_276
col_name: col3
case_id: 1107
Task: Column-type-annotation (source dataset: SemTab2019)

Your task is to annotate the target entity column in the input table with the DBPedia ontology that can most accurately describe all entities in the column (i.e. use the most fine grained ontology class name that can describe all entities in the column).

No explanation, return the ontology class in JSON format: {"DBpedia ontology class": "<DBpedia ontology class>"}. Please note that DBpedia ontology classes are in the format of "http://dbpedia.org/ontology/<class_name>".

Input Table:
| col0                          | col1                     | col2        | col3                     |
|:------------------------------|:-------------------------|:------------|:-------------------------|
| 1934 German Grand Prix        | Auto Union               | H. Stuck    | Mercedes-Benz            |
| 1933 Tunis Grand Prix         | Alfa Romeo in motorsport | T. Nuvolari | Alfa Romeo in motorsport |
| 1933 Penya Rhin Grand Prix    | Bugatti                  | T. Nuvolari | Alfa Romeo in motorsport |
| 1933 Nice Grand Prix          | Maserati                 | T. Nuvolari | Bugatti                  |
| 1933 Monaco Grand Prix        | Bugatti                  | A. Varzi    | Alfa Romeo in motorsport |
| 1933 French Grand Prix        | Maserati in motorsport   | G. Campari  | Alfa Romeo in motorsport |
| 1933 Belgian Grand Prix       | Maserati in motorsport   | T. Nuvolari | Bugatti                  |
| 1932 Tunis Grand Prix         | Bugatti                  | L. Chiron   | Bugatti                  |
| 1932 Nice Circuit Race        | Bugatti                  | R. Dreyfus  | Alfa Romeo               |
| 1932 Monaco Grand Prix        | Bugatti                  | A. Varzi    | Alfa Romeo in motorsport |
| 1932 Italian Grand Prix       | Alfa Romeo in motorsport | T. Nuvolari | Maserati                 |
| 1932 German Grand Prix        | Alfa Romeo in motorsport | T. Nuvolari | Alfa Romeo in motorsport |
| 1932 French Grand Prix        | Alfa Romeo in motorsport | T. Nuvolari | Alfa Romeo in motorsport |
| 1931 Monaco Grand Prix        | Bugatti                  | L. Chiron   | Maserati in motorsport   |
| 1931 Italian Grand Prix       | Alfa Romeo in motorsport | G. Campari  | Alfa Romeo in motorsport |
| 1931 German Grand Prix        | Bugatti                  | A. Varzi    | Bugatti                  |
| 1931 French Grand Prix        | Maserati                 | L. Fagioli  | Alfa Romeo in motorsport |
| 1931 Belgian Grand Prix       | Bugatti                  | L. Chiron   | Alfa Romeo in motorsport |
| 1930 San Sebastián Grand Prix | Maserati in motorsport   | A. Varzi    | Maserati in motorsport   |
| 1930 Rome Grand Prix          | Bugatti                  | L. Chiron   | Bugatti                  |
| 1930 Monza Grand Prix         | Maserati in motorsport   | A. Varzi    | Maserati in motorsport   |
| 1930 Monaco Grand Prix        | Bugatti                  | R. Dreyfus  | Bugatti                  |

Target entity column: col1



col_id: 1
label: http://dbpedia.org/ontology/Company
okay_annotation: http://dbpedia.org/ontology/Organisation
csv: v16_346
col_name: col1
case_id: 679