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U4RASD/
DRU-RE-EntityPair-TwoHead

Name: DRU-RE-EntityPair-TwoHead
Availability: InStock

U4RASD/WojoodRelationsAnnotated

U4RASD/NeoAraBERT

finetune

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DRU-RE-EntityPair-TwoHead

DRU-RE-EntityPair-TwoHead is an Arabic relation extraction model built on U4RASD/NeoAraBERT for the WojoodRelations / KnowledgeGraphEval relation inventory.

The model predicts whether a relation exists for a subject/object pair, then predicts the positive relation type with a separate head. It expects the subject span, object span, and coarse entity types to be known.

Architecture

The input sentence is marked with typed subject/object markers and encoded with NeoAraBERT. The pair representation is built from:

the contextual CLS vector,
the contextual opening subject-marker vector,
the contextual opening object-marker vector,
the absolute subject/object difference vector,
the elementwise subject/object product vector,
a 42-dimensional directional one-hot entity-type vector.

These features are concatenated into:

5 * encoder_hidden_size + 42 = 5 * 768 + 42 = 3882

That pair vector is passed through a pair MLP:

3882 -> 1024 -> 512

The resulting shared pair representation feeds two heads:

a binary existence head: no_relation vs relation_exists
a 40-way positive-relation head: only positive labels, no no_relation class

Training behavior:

for no_relation rows, only the existence loss is active
for positive rows, both the existence loss and positive-label loss are active

Training Setup

Base encoder: U4RASD/NeoAraBERT
Dataset: U4RASD/WojoodRelationsAnnotated
Train file: train.jsonl
Labeled validation file: val.jsonl
Official prediction input: val_official_annotated_unlabeled.jsonl
Max length: 512
Context chars: 300
Epochs: 4
Train batch size: 4
Eval batch size: 8
Gradient accumulation: 4
Effective batch size: 16
Encoder LR: 1e-5
Head LR: 5e-5
Weight decay: 0.01
Warmup ratio: 0.1
Pair dropout: 0.1
Type feature mode: one_hot_42_directional
Existence loss weight: 1.0
Positive relation loss weight: 1.0
Best checkpoint recorded in config:
- outputs/DRU-RE-EntityPair-TwoHead/checkpoints/checkpoint-1500

Labels And Types

Total labels: 41
Positive labels: 40
Coarse entity types: 21

The config and label/type maps are stored in:

configs/run_config.json
configs/architecture_config.json
configs/labels.json
configs/positive_labels.json
configs/entity_types.json
configs/label2id.json, configs/id2label.json
configs/positive_label2id.json, configs/positive_id2label.json
configs/type2id.json, configs/id2type.json

Thresholds

This repo contains two official-style submission variants:

tuned-threshold submission:
- artifacts/submission.zip
- uses existence threshold 0.14
- source: auto_tuned_on_labeled_val
fixed-threshold submission:
- artifacts/submission_threshold_0_5.zip
- uses existence threshold 0.5

The threshold sweep is stored in:

artifacts/existence_threshold_sweep.csv
artifacts/best_existence_threshold.json
artifacts/submission_threshold_0_5_summary.json

From the sweep on labeled val.jsonl:

best positive micro F1: 0.5429333333333334
best threshold: 0.14
labeled-val micro precision: 0.5049603174603174
labeled-val micro recall: 0.5870818915801614
labeled-val all-label accuracy: 0.6277415530527564

From the fixed 0.5 summary:

total rows: 2074
no_relation predictions: 1322
changed vs threshold 0.14: 414

Input Contract

Each example is expected to provide:

sentence
subject
object
subject_start
subject_end
object_start
object_end
subject_type
object_type

The official evaluation input should come from:

U4RASD/WojoodRelationsAnnotated/val_official_annotated_unlabeled.jsonl

That file keeps the official validation row set and order, includes spans/types, and intentionally leaves relation blank.

Output Contract

For Codabench-style submission, write:

<triple_id>\t<predicted_relation>

When the internal prediction is no_relation, the submission file should use Codabench's spelling:

no-relation

This repo already includes:

artifacts/predictions.txt
artifacts/predictions_threshold_0_5.txt
artifacts/submission.zip
artifacts/submission_threshold_0_5.zip
artifacts/codabench_val_predictions.jsonl
artifacts/codabench_val_predictions_debug.jsonl

Files

model/pytorch_model.bin: custom PyTorch state dict
model/modeling_entity_pair_two_head.py: model definition
model/config.json: tokenizer/model config metadata
model/tokenizer.json, model/tokenizer_config.json, model/special_tokens_map.json
artifacts/labeled_val_metrics.json
artifacts/labeled_val_classification_report.csv
artifacts/labeled_val_confusion_matrix.csv
artifacts/labeled_val_predictions_debug.jsonl
artifacts/existence_threshold_sweep.csv
artifacts/submission.zip
artifacts/submission_threshold_0_5.zip

Evaluation Notes

The repo stores threshold-aware labeled validation metrics in:

artifacts/labeled_val_metrics.json
artifacts/existence_threshold_sweep.csv
artifacts/best_existence_threshold.json

The main model-selection metric recorded in run_config.json is the same value reported in the labeled validation metrics:

best_metric = micro_f1_positive = 0.5429333333333334

This corresponds to the tuned existence threshold 0.14 on labeled val.jsonl.

Practical Use

Use this model when:

you have reliable subject/object spans,
you have reliable coarse entity types,
you want a stronger binary relation detector than the older one-head DRU-RE variants,
you want access to both a tuned official submission and a stricter 0.5 threshold submission.

Limitations

This is not a general-purpose Arabic RE model for arbitrary schemas.
It is tied to the WojoodRelations label inventory and preprocessing assumptions.
Performance depends heavily on correct spans and correct coarse entity types.
The existence threshold changes behavior materially. 0.14 and 0.5 are meaningfully different operating points.

Provenance

Dataset: https://huggingface.co/datasets/U4RASD/WojoodRelationsAnnotated
Base encoder: https://huggingface.co/U4RASD/NeoAraBERT
Wojood / ArabicNER: https://github.com/SinaLab/ArabicNER
WojoodRelations paper: https://aclanthology.org/2025.emnlp-main.1741/
Sina relation tools: https://sina.birzeit.edu/relations/

U4RASD/DRU-RE-EntityPair-TwoHead