README.md

metadata

license: apache-2.0
task_categories:
  - text-classification
task_ids:
  - multi-label-classification
language:
  - es
multilinguality:
  - monolingual
size_categories:
  - n<1K
pretty_name: DISCOPALAffectClassification
tags:
  - poetry
  - spanish
  - sonnet
  - affect
  - emotion-classification
  - multi-label-classification
  - disco
  - disco-pal
  - mteb
  - poetrymteb
  - embedding-evaluation
annotations_creators:
  - expert-generated
source_datasets:
  - DISCO PAL
  - DISCO
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*
    default: true
dataset_info:
  - config_name: default
    features:
      - name: id
        dtype: string
      - name: source_index
        dtype: int64
      - name: poem
        dtype: string
      - name: labels
        sequence: int64
      - name: label_names
        sequence: string
      - name: scores
        sequence: float64
      - name: dimensional_scores
        sequence: float64
      - name: dimensional_names
        sequence: string
      - name: n_annotators
        dtype: int64
    splits:
      - name: train
        num_examples: 219
      - name: test
        num_examples: 55

DISCOPALAffectClassification

Multi-label affect / emotion classification over Spanish sonnets for PoetryMTEB, derived from DISCO PAL (Barbado et al., 2020).

Each poem is a classical soneto from the diachronic Spanish sonnet corpus DISCO, annotated by three POSTDATA (UNED) domain experts for evoked affect on a 1–4 intensity scale. We aggregate with the official median file (poems_corpus_all.csv) and binarize the five basic emotions for embedding evaluation.

Dataset Card

Item	Description
Source annotations	DISCO PAL (Processed Annotations/poems_corpus_all.csv)
Source poems	DISCO (Diachronic Spanish Sonnet Corpus)
Paper	Barbado et al., DISCO PAL: Diachronic Spanish Sonnet Corpus with Psychological and Affective Labels, arXiv:2007.04626
Languages	Spanish (es)
Unit	Full sonnet text (poem)
Labels	Multi-label subset of 5 basic emotions (Happiness, Sadness, Anger, Fear, Disgust)
Score scale	Continuous intensities 1–4 (evoked affect); median of 3 experts
Size	train=219; test=55
Splits	Stratified by primary (highest-score) affect ≈ 80% / 20%, seed=42
License	Apache License 2.0 (DISCO PAL project)
Evaluation metrics	Multi-label classification on embeddings: macro/micro F1, Average Precision (AP)

Label binarization

Absolute thresholds on the 1–4 scale leave many poems with no positive emotion (e.g. score ≥ 3 empties ~45% of poems). Following the PoetryMTEB POCA pipeline, we therefore use relative within-poem salience:

1. Take the five emotion intensities (median over experts).
2. Compute within-poem z-scores; keep emotions with (z \ge 1.0).
3. Always include the top-1 emotion (guarantees ≥1 label).

Mean labels/poem ≈ 1.22.

Auxiliary dimensional ratings (Valence, Arousal, Concreteness, Imageability, Context Availability) are stored as continuous scores for analysis; they are not classification targets in this release.

Label taxonomy (5)

id	label_name (en)	es	zh	train	test	total
0	Happiness	Alegría	喜悦	86	22	108
1	Sadness	Tristeza	悲伤	125	33	158
2	Anger	Ira	愤怒	14	4	18
3	Fear	Miedo	恐惧	10	2	12
4	Disgust	Asco	厌恶	30	8	38

Codebook: label_taxonomy.json.

Dimensional scores (auxiliary)

name (en)	es	zh	scale
Valence	Valencia	效价	1–4 (median of 3 experts)
Arousal	Activación	唤醒度	1–4 (median of 3 experts)
Concreteness	Concreción	具体性	1–4 (median of 3 experts)
Imageability	Imaginabilidad	意象性	1–4 (median of 3 experts)
ContextAvailability	Disponibilidad contextual	语境可得性	1–4 (median of 3 experts)

Features

Field	Type	Description
id	string	Example id (discopal-affect-{source_index})
source_index	int64	Row index in upstream poems_corpus_all.csv
poem	string	Full Spanish sonnet text (classification input)
labels	list[int64]	Emotion class indices
label_names	list[string]	Canonical English emotion names
scores	list[float64]	Median intensities for the 5 emotions (taxonomy order, 1–4)
dimensional_scores	list[float64]	Median dimensional ratings (order = dimensional_names)
dimensional_names	list[string]	Names of dimensional dimensions
n_annotators	int64	Number of experts aggregated (3; median)

Construction method

1. Load poems_corpus_all.csv (median of annotators a1/a2/a3).
2. Normalize column names (strip whitespace / NBSP artifacts).
3. Map source columns (happinness typo preserved upstream → Happiness) to the 5-emotion taxonomy.
4. Binarize with within-poem (z \ge 1.0) + top-1.
5. Stratified train/test split by primary affect (seed=42).

Intended use

Designed for PoetryMTEB / MTEB-style multi-label classification probing of poem embeddings in Spanish. Not a clinical diagnostic resource; psychological companion labels are released separately as DISCOPALPsychClassification.

Citation

@article{barbado2020disco,
  title={DISCO PAL: Diachronic Spanish Sonnet Corpus with Psychological and Affective Labels},
  author={Barbado, Alberto and Fresno, Víctor and Riesco, Ángeles Manjarrés and Ros, Salvador},
  journal={arXiv preprint arXiv:2007.04626},
  year={2020}
}

Please also cite the underlying sonnet corpus:

@misc{disco2017,
  author={Ruiz Fabo, Pablo and Bermúdez Sabel, Helena and Martínez Cantón, Clara and Calvo Tello, José},
  title={Diachronic Spanish Sonnet Corpus (DISCO)},
  year={2017},
  howpublished={UNED / Zenodo},
  doi={10.5281/zenodo.1069844},
  url={https://github.com/pruizf/disco}
}

License

Apache License 2.0 for DISCO PAL annotations and this redistribution. Poem texts originate from DISCO; respect upstream DISCO terms when redistributing full texts beyond research evaluation use.