Triple

T19504363
Position Surface form Disambiguated ID Type / Status
Subject Daniel Marhely E487980 entity
Predicate name P16 FINISHED
Object Daniel Marhely NE NERFINISHED

How this triple was built (2 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: [Daniel Marhely, name, Daniel Marhely]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daniel Marhely
Context triple: [Daniel Marhely, name, Daniel Marhely]
  • A. Daniel Marhely chosen
    Daniel Marhely is a French tech entrepreneur best known for co-founding the music streaming service Deezer.
  • B. Marcell Rév
    Marcell Rév is a Hungarian cinematographer known for his visually striking, atmospheric work on films and series such as "Malcolm & Marie" and "Euphoria."
  • C. David Palffy
    David Palffy is a Canadian actor best known for his recurring villain roles on the science fiction television series Stargate SG-1.
  • D. Bruno Pésery
    Bruno Pésery is a French film producer known for his work on notable art-house and auteur-driven films.
  • E. Daniel Balint
    Daniel Balint is the conflicted neo-Nazi protagonist of the film "The Believer," whose Jewish heritage drives a profound internal struggle over faith, identity, and self-hatred.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d9d1c88190b01cd78b8be49384 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e635105db8819084915dc2d047188d completed April 20, 2026, 2:15 p.m.
Created at: April 10, 2026, 1:40 p.m.