README.md

---
dataset_info:
- config_name: ee
  features:
  - name: id
    dtype: string
  - name: text
    dtype: string
  - name: entity_mentions
    list:
    - name: id
      dtype: string
    - name: text
      dtype: string
    - name: start
      dtype: int64
    - name: end
      dtype: int64
    - name: char_start
      dtype: int64
    - name: char_end
      dtype: int64
    - name: type
      dtype: string
  - name: event_mentions
    list:
    - name: id
      dtype: string
    - name: trigger
      struct:
      - name: text
        dtype: string
      - name: start
        dtype: int64
      - name: end
        dtype: int64
      - name: char_start
        dtype: int64
      - name: char_end
        dtype: int64
    - name: arguments
      list:
      - name: text
        dtype: string
      - name: start
        dtype: int64
      - name: end
        dtype: int64
      - name: char_start
        dtype: int64
      - name: char_end
        dtype: int64
      - name: role
        dtype: string
      - name: type
        dtype: string
    - name: event_type
      dtype: string
  - name: tokens
    sequence: string
  - name: pos_tags
    sequence: string
  - name: lemma
    sequence: string
  - name: ner_tags
    sequence: string
  splits:
  - name: train
    num_bytes: 6532239
    num_examples: 1861
  - name: validation
    num_bytes: 792697
    num_examples: 228
  - name: test
    num_bytes: 802322
    num_examples: 230
  download_size: 3171788
  dataset_size: 8127258
- config_name: ner
  features:
  - name: id
    dtype: string
  - name: tokens
    sequence: string
  - name: ner_tags
    sequence: string
  splits:
  - name: train
    num_bytes: 2062754
    num_examples: 1861
  - name: validation
    num_bytes: 250635
    num_examples: 228
  - name: test
    num_bytes: 255164
    num_examples: 230
  download_size: 736425
  dataset_size: 2568553
- config_name: re
  features:
  - name: id
    dtype: string
  - name: tokens
    sequence: string
  - name: entities
    sequence:
      sequence: int64
  - name: entity_roles
    sequence: string
  - name: entity_types
    sequence: string
  - name: event_type
    dtype: string
  - name: entity_ids
    sequence: string
  splits:
  - name: train
    num_bytes: 2116771
    num_examples: 1007
  - name: validation
    num_bytes: 265248
    num_examples: 129
  - name: test
    num_bytes: 238094
    num_examples: 128
  download_size: 801404
  dataset_size: 2620113
configs:
- config_name: ee
  data_files:
  - split: train
    path: ee/train-*
  - split: validation
    path: ee/validation-*
  - split: test
    path: ee/test-*
- config_name: ner
  data_files:
  - split: train
    path: ner/train-*
  - split: validation
    path: ner/validation-*
  - split: test
    path: ner/test-*
- config_name: re
  data_files:
  - split: train
    path: re/train-*
  - split: validation
    path: re/validation-*
  - split: test
    path: re/test-*
license: cc-by-4.0
task_categories:
- text-classification
- token-classification
language:
- de
tags:
- finance
- relation-extraction
- event-extraction
- traffic
- industry
pretty_name: SmartData Corpus
size_categories:
- 1K<n<10K
---
# Dataset Card for SmartData Corpus

## Dataset Description

- **Repository:** [https://github.com/dfki-nlp/smartdata-corpus](https://github.com/dfki-nlp/smartdata-corpus)
- **Paper:** [A German Corpus for Fine-Grained Named Entity Recognition and Relation Extraction of Traffic and Industry Events](https://www.dfki.de/web/forschung/projekte-publikationen/publikation/9427/)

### Dataset Summary

SmartData Corpus is a German-language dataset which is human-annotated with entity types and a set of 15 traffic- and 
industry-related n-ary relations and events, such as accidents, traffic jams, acquisitions, and strikes. 
The corpus consists of newswire texts, Twitter messages, and traffic reports from radio stations, police and 
railway companies.

This version of the dataset loader provides configurations for:

- Named Entity Recognition (`ner`): NER tags use the `BIO` tagging scheme
- Relation Extraction (`re`): n-ary Relation Extraction
- Event Extraction (`ee`): formatted similar to https://github.com/nlpcl-lab/ace2005-preprocessing?tab=readme-ov-file#format

For more details see https://github.com/dfki-nlp/smartdata-corpus and https://www.dfki.de/web/forschung/projekte-publikationen/publikation/9427/.

### Supported Tasks and Leaderboards

- **Tasks:** Named Entity Recognition, n-ary Relation Extraction, Event Extraction
- **Leaderboards:**

### Languages

German

## Dataset Structure

### Data Instances

#### ner
An example of 'train' looks as follows.

```json
{
  "id": "671734738147758080",
  "tokens": ["A1", "Zwischen", "AS", "Munsbach", "und", "AS", "Flaxweiler", "Bauarbeiten", ",", "rechter", "Fahrstreifen", "gesperrt", ",", "Verkehrsbehinderung", ",", "Dauer", ":", "02.12.2015", "...", "#ACL_A1"],
  "ner_tags": ["B-LOCATION_STREET", "O", "B-LOCATION", "I-LOCATION", "O", "B-LOCATION", "I-LOCATION", "O", "O", "O", "O", "O", "O", "B-TRIGGER", "O", "O", "O", "B-DATE", "O", "B-LOCATION_STREET"]
}
```

#### re
An example of 'train' looks as follows.

```json
{
  "id": "671734738147758080_0",
  "tokens": ["A1", "Zwischen", "AS", "Munsbach", "und", "AS", "Flaxweiler", "Bauarbeiten", ",", "rechter", "Fahrstreifen", "gesperrt", ",", "Verkehrsbehinderung", ",", "Dauer", ":", "02.12.2015", "...", "#ACL_A1"],
  "entities": [[0, 1], [2, 4], [5, 7], [13, 14], [17, 18], [19, 20]],
  "entity_roles": ["location", "start_loc", "end_loc", "trigger", "end_date", "no_arg"],
  "entity_types": ["LOCATION_STREET", "LOCATION", "LOCATION", "TRIGGER", "DATE", "LOCATION_STREET"],
  "event_type": "Obstruction",
  "entity_ids": ["c/ac611f0a-d610-4ab2-9ddf-00132d9374b5", "c/3e01d530-58c4-4f47-9ab3-082a58e8299b", "c/cb6975e8-4409-4bdf-a491-de398b3c3263", "c/684a0ccd-06ff-4a8f-a90f-bdef169077dc", "c/166acddb-0f4d-48eb-98f6-a8b490f2e578", "c/ca3befa0-92da-4ff9-b34d-ec351854cdda"]
}
```

#### ee

An example of 'train' looks as follows.

```json
{
  "id": "671734738147758080",
  "text": "A1 Zwischen AS Munsbach und AS Flaxweiler Bauarbeiten, rechter Fahrstreifen gesperrt, Verkehrsbehinderung, Dauer: 02.12.2015... #ACL_A1\n",
  "entity_mentions": [
    {"id": "c/ac611f0a-d610-4ab2-9ddf-00132d9374b5", "text": "A1", "start": 0, "end": 1, "char_start": 0, "char_end": 2, "type": "LOCATION_STREET"},
    {"id": "c/3e01d530-58c4-4f47-9ab3-082a58e8299b", "text": "AS Munsbach", "start": 2, "end": 4, "char_start": 12, "char_end": 23, "type": "LOCATION"},
    {"id": "c/cb6975e8-4409-4bdf-a491-de398b3c3263", "text": "AS Flaxweiler", "start": 5, "end": 7, "char_start": 28, "char_end": 41, "type": "LOCATION"},
    {"id": "c/684a0ccd-06ff-4a8f-a90f-bdef169077dc", "text": "Verkehrsbehinderung", "start": 13, "end": 14, "char_start": 86, "char_end": 105, "type": "TRIGGER"},
    {"id": "c/166acddb-0f4d-48eb-98f6-a8b490f2e578", "text": "02.12.2015", "start": 17, "end": 18, "char_start": 114, "char_end": 124, "type": "DATE"},
    {"id": "c/ca3befa0-92da-4ff9-b34d-ec351854cdda", "text": "#ACL_A1", "start": 19, "end": 20, "char_start": 128, "char_end": 135, "type": "LOCATION_STREET"}
  ],
  "event_mentions": [
    {
      "id": "r/802a82c2-c214-4429-b9f1-bf56e46674ee",
      "trigger": {
        "text": "Verkehrsbehinderung", "start": 13, "end": 14, "char_start": 86, "char_end": 105
      },
      "arguments": [
        {"text": "02.12.2015", "start": 17, "end": 18, "char_start": 114, "char_end": 124, "role": "end_date", "type": "date"},
        {"text": "AS Flaxweiler", "start": 5, "end": 7, "char_start": 28, "char_end": 41, "role": "end_loc", "type": "location"},
        {"text": "AS Munsbach", "start": 2, "end": 4, "char_start": 12, "char_end": 23, "role": "start_loc", "type": "location"},
        {"text": "A1", "start": 0, "end": 1, "char_start": 0, "char_end": 2, "role": "location", "type": "location-street"}
      ],
      "event_type": "Obstruction"
    }
  ],
  "tokens": ["A1", "Zwischen", "AS", "Munsbach", "und", "AS", "Flaxweiler", "Bauarbeiten", ",", "rechter", "Fahrstreifen", "gesperrt", ",", "Verkehrsbehinderung", ",", "Dauer", ":", "02.12.2015", "...", "#ACL_A1"],
  "pos_tags": ["CARD", "APPR", "NE", "NE", "KON", "NE", "NE", "NN", "$,", "ADJA", "NN", "VVPP", "$,", "NN", "$,", "NN", "$.", "CARD", "$[", "CARD"],
  "lemma": ["a1", "zwischen", "as", "munsbach", "und", "as", "flaxweiler", "bauarbeiten", ",", "rechter", "fahrstreifen", "gesperrt", ",", "verkehrsbehinderung", ",", "dauer", ":", "02.12.2015", "...", "#acl_a1"],
  "ner_tags": ["B-LOCATION_STREET", "O", "B-LOCATION", "I-LOCATION", "O", "B-LOCATION", "I-LOCATION", "O", "O", "O", "O", "O", "O", "B-TRIGGER", "O", "O", "O", "B-DATE", "O", "B-LOCATION_STREET"]
}
```


### Data Fields

#### ner

- `id`: example identifier, a `string` feature.
- `tokens`: list of tokens, a `list` of `string` features.
- `ner_tags`: list of NER tags, a `list` of `string` features.

#### re

- `id`: example identifier, a `string` feature.
- `text`: example text, a `string` feature.
- `tokens`: list of tokens, a `list` of `string` features.
- `entities`: a list of token spans, a `list` of `int64` features.
- `entity_roles`: a `list` of entity roles, a list of `string` features.
- `event_type`: the event type, a `string` feature.
- `entity_ids`: list of entity ids, a `list` of `string` features.

#### ee

- `id`: example identifier, a `string` feature.
- `text`: example text, a `string` feature.
- `entity_mentions`: a `list` of `struct` features.
  - `text`: a `string` feature.
  - `start`: token offset start, a `int64` feature.
  - `end`: token offset end, a `int64` feature.
  - `char_start`: character offset start, a `int64` feature.
  - `char_end`: character offset end, a `int64` feature.
  - `type`: entity type, a `string` feature.
  - `id`: entity id, a `string` feature.
- `event_mentions`: a list of `struct` features.
  - `id`: event identifier, a `string` feature.
  - `trigger`: a `struct` feature.
    - `text`: a `string` feature.
    - `start`: token offset start, a `int64` feature.
    - `end`: token offset end, a `int64` feature.
    - `char_start`: character offset start, a `int64` feature.
    - `char_end`: character offset end, a `int64` feature.
  - `arguments`: a list of `struct` features.
    - `text`: a `string` feature.
    - `start`: token offset start, a `int64` feature.
    - `end`: token offset end, a `int64` feature.
    - `char_start`: character offset start, a `int64` feature.
    - `char_end`: character offset end, a `int64` feature.
    - `role`: role of the argument, a `string` feature.
    - `type`: entity type of the argument, a `string` feature.
  - `event_type`: a classification label, a `string` feature.
- `tokens`: list of tokens, a `list` of `string` features.
- `pos_tags`: list of part-of-speech tags, a `list` of `string` features.
- `lemma`: list of lemmatized tokens, a `list` of `string` features.
- `ner_tags`: a `list` of NER tags, a list of `string` features.

### Licensing Information

[CC BY-SA 4.0 license](https://creativecommons.org/licenses/by-sa/4.0/)

### Citation Information

**BibTeX:**
```
@InProceedings{SCHIERSCH18.85,
  author = {Martin Schiersch and Veselina Mironova and Maximilian Schmitt and Philippe Thomas and Aleksandra Gabryszak and Leonhard Hennig},
  title = "{A German Corpus for Fine-Grained Named Entity Recognition and Relation Extraction of Traffic and Industry Events}",
  booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)},
  year = {2018},
  month = {May 7-12, 2018},
  address = {Miyazaki, Japan},
  editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {979-10-95546-00-9},
  language = {english}
  }
```

**APA:**
- Schiersch, M., Mironova, V., Schmitt, M., Thomas, P., Gabryszak, A., & Hennig, L. (2018). A German Corpus for Fine-Grained Named Entity Recognition and Relation Extraction of Traffic and Industry Events. In N. Calzolari (Conference chair), K. Choukri, C. Cieri, T. Declerck, S. Goggi, K. Hasida, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk, S. Piperidis, & T. Tokunaga (Eds.), Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018) (pp. Unknown). Miyazaki, Japan: European Language Resources Association (ELRA). ISBN: 979-10-95546-00-9.


### Contributions