Triple

T12385459
Position Surface form Disambiguated ID Type / Status
Subject Mourvèdre E295850 entity
Predicate synonym P3575 FINISHED
Object Mataro
Mataro is an alternative name for Mourvèdre, a dark-skinned wine grape variety known for producing robust, tannic red wines often used in Mediterranean and Rhône-style blends.
 E988352 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Mataro | Statement: [Mourvèdre, synonym, Mataro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mataro
Context triple: [Mourvèdre, synonym, Mataro]
  • A. Martorell
    Martorell is a town in Catalonia, Spain, known as an important industrial hub within the Barcelona metropolitan area.
  • B. Barajas
    Barajas is a Madrid Metro station on Line 8 that serves the Barajas district near Madrid–Barajas Airport.
  • C. Alzira
    Alzira is a historic town and municipality in eastern Spain known for its agricultural heritage and location along the Júcar River in the Valencian Community.
  • D. Sesimbra
    Sesimbra is a coastal town and municipality in Portugal known for its fishing heritage, beaches, and proximity to the Arrábida Natural Park.
  • E. Malasaña
    Malasaña is a vibrant central Madrid neighborhood known for its bohemian atmosphere, nightlife, and alternative cultural scene.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Mataro
Triple: [Mourvèdre, synonym, Mataro]
Generated description
Mataro is an alternative name for Mourvèdre, a dark-skinned wine grape variety known for producing robust, tannic red wines often used in Mediterranean and Rhône-style blends.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mataro
Target entity description: Mataro is an alternative name for Mourvèdre, a dark-skinned wine grape variety known for producing robust, tannic red wines often used in Mediterranean and Rhône-style blends.
  • A. Martorell
    Martorell is a town in Catalonia, Spain, known as an important industrial hub within the Barcelona metropolitan area.
  • B. Barajas
    Barajas is a Madrid Metro station on Line 8 that serves the Barajas district near Madrid–Barajas Airport.
  • C. Alzira
    Alzira is a historic town and municipality in eastern Spain known for its agricultural heritage and location along the Júcar River in the Valencian Community.
  • D. Sesimbra
    Sesimbra is a coastal town and municipality in Portugal known for its fishing heritage, beaches, and proximity to the Arrábida Natural Park.
  • E. Malasaña
    Malasaña is a vibrant central Madrid neighborhood known for its bohemian atmosphere, nightlife, and alternative cultural scene.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d6ad9e653c8190b1473c860ee53dae completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d93fbd489c819098233a111442762e completed April 10, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64b926c5c81909427eb191ae75ec6 completed May 2, 2026, 7:08 p.m.
NEDg Description generation batch_69f64da25bf88190889273bf41e2f154 completed May 2, 2026, 7:16 p.m.
NED2 Entity disambiguation (via description) batch_69f65213ed84819086fda178aaf9e774 completed May 2, 2026, 7:35 p.m.
Created at: April 8, 2026, 9:54 p.m.