Triple

T8296564
Position Surface form Disambiguated ID Type / Status
Subject Rosemary Harris E194233 entity
Predicate role P268 FINISHED
Object Aunt May E421823 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: Aunt May | Statement: [Rosemary Harris, role, Aunt May]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aunt May
Context triple: [Rosemary Harris, role, Aunt May]
  • A. Aunt May chosen
    Aunt May is Peter Parker’s loving and morally grounded aunt who serves as a key emotional anchor and guiding influence in the Spider-Man stories.
  • B. Mary Jane Watson
    Mary Jane Watson is a central character in the Spider-Man franchise, best known as Peter Parker’s longtime love interest and a key emotional anchor in his story.
  • C. Helen Burns
    Helen Burns is a pious, patient schoolgirl in Charlotte Brontë’s "Jane Eyre" whose quiet strength and Christian forgiveness deeply influence the young Jane.
  • D. Tante Ju
    Tante Ju is the affectionate nickname for the Junkers Ju 52, a German three-engined transport aircraft widely used in the 1930s and during World War II.
  • E. May Parker (The Amazing Spider-Man film series)
    May Parker in The Amazing Spider-Man film series is Peter Parker’s caring aunt and primary guardian, who provides emotional support and guidance as he grows into his role as Spider-Man.
  • 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_69ca82e50ebc81909aa7b260c76bd757 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7df887148190bddc2609bc885cb4 completed March 31, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd68ad2f248190a1de95c01ddee259 completed April 1, 2026, 6:49 p.m.
Created at: March 30, 2026, 5:53 p.m.