Triple

T20384907
Position Surface form Disambiguated ID Type / Status
Subject Almost Angels E497933 entity
Predicate hasCastMember P2308 FINISHED
Object Peter Weck 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: Peter Weck | Statement: [Almost Angels, hasCastMember, Peter Weck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peter Weck
Context triple: [Almost Angels, hasCastMember, Peter Weck]
  • A. Peter Weck chosen
    Peter Weck is an Austrian actor and director known for his extensive work in German-language film, television, and theater.
  • B. Matthias Weckmann
    Matthias Weckmann was a 17th-century German composer and organist known for his expressive sacred music and significant contributions to the North German organ tradition.
  • C. Harry Weese
    Harry Weese was a prominent 20th-century American architect known for his modernist designs and influential work on projects such as the Washington Metro system.
  • D. Peter Weibel
    Peter Weibel was an influential Austrian artist, curator, and media theorist known for his pioneering work in conceptual and media art and his leadership roles in major European art institutions.
  • E. Thomas Wöbke
    Thomas Wöbke is a German screenwriter and film producer known for his work on various European genre and arthouse films.
  • 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_69e0b4a71ebc8190b153a36c738730f4 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6790a31a4819099b2e6df2bafe547 completed April 20, 2026, 7:05 p.m.
Created at: April 16, 2026, 11:28 a.m.