Triple

T19455709
Position Surface form Disambiguated ID Type / Status
Subject Damsel E486726 entity
Predicate title P38 FINISHED
Object Damsel 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: Damsel | Statement: [Damsel, title, Damsel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Damsel
Context triple: [Damsel, title, Damsel]
  • A. Damsel
    Damsel is a 2024 dark fantasy adventure film starring Millie Bobby Brown as a princess who must fight for survival after being sacrificed to a dragon.
  • B. Damsel chosen
    Damsel is a 2018 offbeat Western dark comedy film directed by David and Nathan Zellner, starring Robert Pattinson and Mia Wasikowska.
  • C. Enchant
    Enchant is an American progressive rock band known for its melodic, guitar-driven sound and intricate song structures.
  • D. Damsels in Distress
    Damsels in Distress is a 2011 indie comedy film written and directed by Whit Stillman that follows a group of college women attempting to improve their campus’s social life and mental health culture.
  • E. Briar Rose
    Briar Rose is a fairy-tale princess figure best known as the enchanted, long-sleeping heroine in adaptations of the Sleeping Beauty story.
  • 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_69d8e8d86d608190bd199a98d0297f27 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e633c2b1108190b492ca23487b91f8 completed April 20, 2026, 2:10 p.m.
Created at: April 10, 2026, 1:38 p.m.