Triple

T3794225
Position Surface form Disambiguated ID Type / Status
Subject Coal Hill Academy E89728 entity
Predicate hasStaffMember P36133 FINISHED
Object Miss Quill E83677 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: Miss Quill | Statement: [Coal Hill Academy, hasStaffMember, Miss Quill]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Miss Quill
Context triple: [Coal Hill Academy, hasStaffMember, Miss Quill]
  • A. Miss Quill chosen
    Miss Quill is a sharp-tongued, battle-hardened alien freedom fighter and teacher from the Doctor Who spin-off series "Class."
  • B. Cassie Lang
    Cassie Lang is a Marvel Comics character best known as Scott Lang’s daughter who becomes the size-changing superheroine Stature (and later Stinger).
  • C. Jennifer Walters
    Jennifer Walters is a Marvel Comics lawyer who becomes the superhero She-Hulk after receiving a blood transfusion from her cousin Bruce Banner.
  • D. Wanda
    Wanda is a feminine given name of Slavic origin, particularly common in Poland and other Central and Eastern European countries.
  • E. Scarlet Witch
    Scarlet Witch is a powerful Marvel Comics superhero and Avenger, known for her reality-warping chaos magic and complex moral journey.
  • 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_69aed9597d6881909b6ee3b9de859223 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aee76b809c81908312f308fbe85bf4 completed March 9, 2026, 3:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4f05c0f908190b5638e75b06dab4d completed March 14, 2026, 5:21 a.m.
Created at: March 9, 2026, 3:15 p.m.