Triple

T23464868
Position Surface form Disambiguated ID Type / Status
Subject Rust and Bone E569076 entity
Predicate castMember P1668 FINISHED
Object Matthias Schoenaerts 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: Matthias Schoenaerts | Statement: [Rust and Bone, castMember, Matthias Schoenaerts]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matthias Schoenaerts
Context triple: [Rust and Bone, castMember, Matthias Schoenaerts]
  • A. Matthias Schoenaerts chosen
    Matthias Schoenaerts is a Belgian actor known for his intense, versatile performances in European cinema and international films such as "Rust and Bone," "Bullhead," and "Far from the Madding Crowd."
  • B. Julien Schoenaerts
    Julien Schoenaerts was a prominent Belgian actor known for his powerful stage and film performances and as one of the leading figures in Flemish theatre.
  • C. Michiel Huisman
    Michiel Huisman is a Dutch actor and musician known for roles in international film and television, including series like Game of Thrones and The Haunting of Hill House.
  • D. Willem Huisman
    Willem Huisman is a notable individual who carries the Dutch surname Huisman, recognized as a distinguished bearer of that name.
  • E. Jeroen Huisman
    Jeroen Huisman is a scholar known for his research on higher education policy, governance, and organization.
  • 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_69e2458ebd808190b3298163132cfb0b completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a6f9e59081909e8cf224ee46109c completed April 29, 2026, 6:36 a.m.
Created at: April 17, 2026, 5:54 p.m.