Triple

T21387867
Position Surface form Disambiguated ID Type / Status
Subject Sergio Marquina E527553 entity
Predicate familyName P18 FINISHED
Object Marquina
Marquina is a Spanish surname most notably associated with the character Sergio Marquina (known as "The Professor") from the television series *Money Heist*.
 E1480670 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: Marquina | Statement: [Sergio Marquina, familyName, Marquina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Marquina
Context triple: [Sergio Marquina, familyName, Marquina]
  • A. Royo
    Royo is the surname of American actor Andre Royo, best known for his role as Bubbles on the television series "The Wire."
  • B. Vacqueyras
    Vacqueyras is a renowned southern Rhône wine appellation in France known for its robust red wines primarily based on Grenache, Syrah, and Mourvèdre.
  • C. Marmolèda
    Marmolèda is the Ladin name for Marmolada, the highest mountain in the Dolomites of northeastern Italy.
  • D. Alcaës
    Alcaës is a figure from Greek mythology, likely a minor or variant character associated with the mythological traditions surrounding Lysidice.
  • E. Senillosa
    Senillosa is a small town in Argentina’s Neuquén Province, known for its agricultural activities and proximity to the city of Neuquén.
  • 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: Marquina
Triple: [Sergio Marquina, familyName, Marquina]
Generated description
Marquina is a Spanish surname most notably associated with the character Sergio Marquina (known as "The Professor") from the television series *Money Heist*.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Marquina
Target entity description: Marquina is a Spanish surname most notably associated with the character Sergio Marquina (known as "The Professor") from the television series *Money Heist*.
  • A. Royo
    Royo is the surname of American actor Andre Royo, best known for his role as Bubbles on the television series "The Wire."
  • B. Vacqueyras
    Vacqueyras is a renowned southern Rhône wine appellation in France known for its robust red wines primarily based on Grenache, Syrah, and Mourvèdre.
  • C. Marmolèda
    Marmolèda is the Ladin name for Marmolada, the highest mountain in the Dolomites of northeastern Italy.
  • D. Alcaës
    Alcaës is a figure from Greek mythology, likely a minor or variant character associated with the mythological traditions surrounding Lysidice.
  • E. Senillosa
    Senillosa is a small town in Argentina’s Neuquén Province, known for its agricultural activities and proximity to the city of Neuquén.
  • 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_69e0b51ff3748190935c0a513c62a12b completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69ee62cb05288190a894f33850e22c03 completed April 26, 2026, 7:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a09b42a4fa88190a167206cedb206ab completed May 17, 2026, 12:27 p.m.
NEDg Description generation batch_6a09b4bd826c8190968bc43f22a5a290 completed May 17, 2026, 12:29 p.m.
NED2 Entity disambiguation (via description) batch_6a09b543ce9881909073c30b7749757b completed May 17, 2026, 12:32 p.m.
Created at: April 16, 2026, 5:12 p.m.