Triple

T10395000
Position Surface form Disambiguated ID Type / Status
Subject Frank (2014 film) E244987 entity
Predicate distributor P1951 FINISHED
Object Element Pictures E257162 NE FINISHED

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: Element Pictures | Statement: [Frank (2014 film), distributor, Element Pictures]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Element Pictures
Context triple: [Frank (2014 film), distributor, Element Pictures]
  • A. Element Pictures chosen
    Element Pictures is an Irish film and television production company known for acclaimed works such as "Room," "The Favourite," and collaborations with director Yorgos Lanthimos.
  • B. Polygon Pictures
    Polygon Pictures is a Japanese animation studio known for its 3D CGI work on numerous anime series and international co-productions.
  • C. The Graphic
    The Graphic was a British illustrated weekly newspaper of the late 19th and early 20th centuries, renowned for its high-quality artwork and influential social commentary.
  • D. Figures
    "Figures" is a soulful, emotionally raw breakup ballad by Canadian singer-songwriter Jessie Reyez that helped launch her into wider recognition.
  • E. Phoenix Pictures
    Phoenix Pictures is an American film production company known for producing critically acclaimed movies such as "Black Swan" and "The Thin Red Line."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d381b5116081908d85227bab6d3c0c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9ce6bb08190bfeaba98a126526d completed April 7, 2026, 11:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69d795c8271c81908a6b67822050c06d completed April 9, 2026, 12:04 p.m.
Created at: April 6, 2026, 12:06 p.m.