Triple

T8458504
Position Surface form Disambiguated ID Type / Status
Subject Mark Ruffalo E199979 entity
Predicate notableWork P4 FINISHED
Object Poor Things E142424 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: Poor Things | Statement: [Mark Ruffalo, notableWork, Poor Things]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Poor Things
Context triple: [Mark Ruffalo, notableWork, Poor Things]
  • A. Poor Things chosen
    Poor Things is a 2023 surreal black comedy fantasy film directed by Yorgos Lanthimos, in which Emma Stone stars as a resurrected woman undergoing a bizarre journey of self-discovery.
  • B. Crimson Peak
    Crimson Peak is a 2015 gothic romance horror film directed by Guillermo del Toro, known for its lavish Victorian production design, ghostly atmosphere, and twisted family drama.
  • C. Gothika
    Gothika is a 2003 supernatural psychological horror film starring Halle Berry as a criminal psychologist who becomes a patient in her own mental institution after a mysterious, possibly paranormal incident.
  • D. Vivarium
    Vivarium is a 2019 science fiction psychological horror film in which a couple becomes trapped in a mysterious, labyrinthine suburban housing development.
  • E. Marwencol
    Marwencol is a 2010 documentary film that follows Mark Hogancamp, a man who copes with trauma by building and photographing an intricate World War II-era miniature town in his backyard.
  • 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_69ca83198c4c8190a337bf717d1813f5 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe49064f881909391d565b97e9886 completed March 31, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce1dea01c481909496ebfca4e9916e completed April 2, 2026, 7:42 a.m.
Created at: March 30, 2026, 6:10 p.m.