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Github: datasets/trec_spanish.py

ir_datasets: TREC Spanish

Index
  1. trec-spanish
  2. trec-spanish/trec3
  3. trec-spanish/trec4

Data Access Information

To use this dataset, you need a copy of the source corpus, provided by the the Linguistic Data Consortium. The specific resource needed is LDC2000T51.

Many organizations already have a subscription to the LDC, so access to the collection can be as easy as confirming the data usage agreement and downloading the corpus. Check with your library for access details.

The source file is: LDC2000T51.tgz.

ir_datasets expects this file to be copied/linked as ~/.ir_datasets/trec-spanish/corpus.tgz.

"trec-spanish"

A collection of news articles in Spanish, used for multi-lingual evaluation in TREC 3 and TREC 4.

Document collection from LDC2000T51.

docs
121K docs

Language: es

Document type:
TrecDoc: (namedtuple)
  1. doc_id: str
  2. text: str
  3. marked_up_doc: str

Examples:

Python API 
import ir_datasets
dataset = ir_datasets.load("trec-spanish")
for doc in dataset.docs_iter():
    doc # namedtuple<doc_id, text, marked_up_doc>

You can find more details about the Python API here.

CLI 
ir_datasets export trec-spanish docs
[doc_id]    [text]    [marked_up_doc]
...

You can find more details about the CLI here.

PyTerrier

No example available for PyTerrier

Citation

ir_datasets.bib:

\cite{Rogers2000Spanish}

Bibtex:

@misc{Rogers2000Spanish, title={TREC Spanish LDC2000T51}, author={Rogers, Willie}, year={2000}, url={https://catalog.ldc.upenn.edu/LDC2000T51}, publisher={Linguistic Data Consortium} }
Metadata 
{
  "docs": {
    "count": 120605,
    "fields": {
      "doc_id": {
        "max_len": 13,
        "common_prefix": ""
      }
    }
  }
}

"trec-spanish/trec3"

Spanish benchmark from TREC 3.

queries
25 queries

Language: multiple/other/unknown

Query type:
TrecSpanish3Query: (namedtuple)
  1. query_id: str
  2. title_es: str
  3. title_en: str
  4. description_es: str
  5. description_en: str
  6. narrative_es: str
  7. narrative_en: str

Examples:

Python API 
import ir_datasets
dataset = ir_datasets.load("trec-spanish/trec3")
for query in dataset.queries_iter():
    query # namedtuple<query_id, title_es, title_en, description_es, description_en, narrative_es, narrative_en>

You can find more details about the Python API here.

CLI 
ir_datasets export trec-spanish/trec3 queries
[query_id]    [title_es]    [title_en]    [description_es]    [description_en]    [narrative_es]    [narrative_en]
...

You can find more details about the CLI here.

PyTerrier

No example available for PyTerrier

docs
121K docs

Inherits docs from trec-spanish

Language: es

Document type:
TrecDoc: (namedtuple)
  1. doc_id: str
  2. text: str
  3. marked_up_doc: str

Examples:

Python API 
import ir_datasets
dataset = ir_datasets.load("trec-spanish/trec3")
for doc in dataset.docs_iter():
    doc # namedtuple<doc_id, text, marked_up_doc>

You can find more details about the Python API here.

CLI 
ir_datasets export trec-spanish/trec3 docs
[doc_id]    [text]    [marked_up_doc]
...

You can find more details about the CLI here.

PyTerrier

No example available for PyTerrier

qrels
19K qrels
Query relevance judgment type:
TrecQrel: (namedtuple)
  1. query_id: str
  2. doc_id: str
  3. relevance: int
  4. iteration: str

Relevance levels

Rel.DefinitionCount%
0not relevant14K74.9%
1relevant4.8K25.1%

Examples:

Python API 
import ir_datasets
dataset = ir_datasets.load("trec-spanish/trec3")
for qrel in dataset.qrels_iter():
    qrel # namedtuple<query_id, doc_id, relevance, iteration>

You can find more details about the Python API here.

CLI 
ir_datasets export trec-spanish/trec3 qrels --format tsv
[query_id]    [doc_id]    [relevance]    [iteration]
...

You can find more details about the CLI here.

PyTerrier

No example available for PyTerrier

Citation

ir_datasets.bib:

\cite{Harman1994Trec3,Rogers2000Spanish}

Bibtex:

@inproceedings{Harman1994Trec3, title={Overview of the Third Text REtrieval Conference (TREC-3)}, author={Donna Harman}, booktitle={TREC}, year={1994} } @misc{Rogers2000Spanish, title={TREC Spanish LDC2000T51}, author={Rogers, Willie}, year={2000}, url={https://catalog.ldc.upenn.edu/LDC2000T51}, publisher={Linguistic Data Consortium} }
Metadata 
{
  "docs": {
    "count": 120605,
    "fields": {
      "doc_id": {
        "max_len": 13,
        "common_prefix": ""
      }
    }
  },
  "queries": {
    "count": 25
  },
  "qrels": {
    "count": 19005,
    "fields": {
      "relevance": {
        "counts_by_value": {
          "1": 4766,
          "0": 14239
        }
      }
    }
  }
}

"trec-spanish/trec4"

Spanish benchmark from TREC 4.

queries
25 queries

Language: multiple/other/unknown

Query type:
TrecSpanish4Query: (namedtuple)
  1. query_id: str
  2. description_es1: str
  3. description_en1: str
  4. description_es2: str
  5. description_en2: str

Examples:

Python API 
import ir_datasets
dataset = ir_datasets.load("trec-spanish/trec4")
for query in dataset.queries_iter():
    query # namedtuple<query_id, description_es1, description_en1, description_es2, description_en2>

You can find more details about the Python API here.

CLI 
ir_datasets export trec-spanish/trec4 queries
[query_id]    [description_es1]    [description_en1]    [description_es2]    [description_en2]
...

You can find more details about the CLI here.

PyTerrier

No example available for PyTerrier

docs
121K docs

Inherits docs from trec-spanish

Language: es

Document type:
TrecDoc: (namedtuple)
  1. doc_id: str
  2. text: str
  3. marked_up_doc: str

Examples:

Python API 
import ir_datasets
dataset = ir_datasets.load("trec-spanish/trec4")
for doc in dataset.docs_iter():
    doc # namedtuple<doc_id, text, marked_up_doc>

You can find more details about the Python API here.

CLI 
ir_datasets export trec-spanish/trec4 docs
[doc_id]    [text]    [marked_up_doc]
...

You can find more details about the CLI here.

PyTerrier

No example available for PyTerrier

qrels
13K qrels
Query relevance judgment type:
TrecQrel: (namedtuple)
  1. query_id: str
  2. doc_id: str
  3. relevance: int
  4. iteration: str

Relevance levels

Rel.DefinitionCount%
0not relevant11K83.2%
1relevant2.2K16.8%

Examples:

Python API 
import ir_datasets
dataset = ir_datasets.load("trec-spanish/trec4")
for qrel in dataset.qrels_iter():
    qrel # namedtuple<query_id, doc_id, relevance, iteration>

You can find more details about the Python API here.

CLI 
ir_datasets export trec-spanish/trec4 qrels --format tsv
[query_id]    [doc_id]    [relevance]    [iteration]
...

You can find more details about the CLI here.

PyTerrier

No example available for PyTerrier

Citation

ir_datasets.bib:

\cite{Harman1995Trec4,Rogers2000Spanish}

Bibtex:

@inproceedings{Harman1995Trec4, title={Overview of the Fourth Text REtrieval Conference (TREC-4)}, author={Donna Harman}, booktitle={TREC}, year={1995} } @misc{Rogers2000Spanish, title={TREC Spanish LDC2000T51}, author={Rogers, Willie}, year={2000}, url={https://catalog.ldc.upenn.edu/LDC2000T51}, publisher={Linguistic Data Consortium} }
Metadata 
{
  "docs": {
    "count": 120605,
    "fields": {
      "doc_id": {
        "max_len": 13,
        "common_prefix": ""
      }
    }
  },
  "queries": {
    "count": 25
  },
  "qrels": {
    "count": 13109,
    "fields": {
      "relevance": {
        "counts_by_value": {
          "1": 2202,
          "0": 10907
        }
      }
    }
  }
}