Triple

T5028937
Position Surface form Disambiguated ID Type / Status
Subject Deezer E113247 entity
Predicate founder P104 FINISHED
Object Daniel Marhely
Daniel Marhely is a French tech entrepreneur best known for co-founding the music streaming service Deezer.
E487980 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: Daniel Marhely | Statement: [Deezer, founder, Daniel Marhely]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daniel Marhely
Context triple: [Deezer, founder, Daniel Marhely]
  • A. Marton Csokas
    Marton Csokas is a New Zealand actor known for his versatile character roles in international films and television series, including major action and fantasy franchises.
  • B. Ferenc Dávid
    Ferenc Dávid was a 16th-century Transylvanian religious reformer and theologian who became a leading figure of early Unitarianism and a pioneer of religious tolerance in Europe.
  • C. Andrej Meszároš
    Andrej Meszároš is a Slovak professional ice hockey defenceman who has played in the NHL and internationally for the Slovak national team.
  • D. Daniel Tarschys
    Daniel Tarschys is a Swedish political scientist and politician who served as Secretary General of the Council of Europe in the 1990s.
  • E. Andreas Homoki
    Andreas Homoki is a prominent Swiss opera director and cultural manager, known for leading major European opera houses and shaping contemporary opera productions.
  • 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: Daniel Marhely
Triple: [Deezer, founder, Daniel Marhely]
Generated description
Daniel Marhely is a French tech entrepreneur best known for co-founding the music streaming service Deezer.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Daniel Marhely
Target entity description: Daniel Marhely is a French tech entrepreneur best known for co-founding the music streaming service Deezer.
  • A. Marton Csokas
    Marton Csokas is a New Zealand actor known for his versatile character roles in international films and television series, including major action and fantasy franchises.
  • B. Ferenc Dávid
    Ferenc Dávid was a 16th-century Transylvanian religious reformer and theologian who became a leading figure of early Unitarianism and a pioneer of religious tolerance in Europe.
  • C. Andrej Meszároš
    Andrej Meszároš is a Slovak professional ice hockey defenceman who has played in the NHL and internationally for the Slovak national team.
  • D. Daniel Tarschys
    Daniel Tarschys is a Swedish political scientist and politician who served as Secretary General of the Council of Europe in the 1990s.
  • E. Andreas Homoki
    Andreas Homoki is a prominent Swiss opera director and cultural manager, known for leading major European opera houses and shaping contemporary opera productions.
  • 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_69bd443775e48190a646ffbfc4334723 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd738f2cc88190a03eebf19e407411 completed March 20, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69be9c6859a88190bbf5688812f2eb91 completed March 21, 2026, 1:26 p.m.
NEDg Description generation batch_69be9e13855081908c3adc9c5c9f3b2d completed March 21, 2026, 1:33 p.m.
NED2 Entity disambiguation (via description) batch_69be9e83b6e48190b56eb02fce41bbf0 completed March 21, 2026, 1:34 p.m.
Created at: March 20, 2026, 1:36 p.m.