Triple

T32007231
Position Surface form Disambiguated ID Type / Status
Subject Elizabeth Hughes E817301 entity
Predicate hasBiographicalGenre P30869 FINISHED
Object medical biography LITERAL 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: medical biography | Statement: [Elizabeth Hughes, hasBiographicalGenre, medical biography]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasBiographicalGenre
Context triple: [Elizabeth Hughes, hasBiographicalGenre, medical biography]
  • A. hasBiographicalTheme
    Indicates that something (such as a work, text, or content) centers on or significantly involves biographical subject matter, such as a person’s life, experiences, or personal history.
  • B. hasBiographicalStyle
    Indicates that something is characterized by or presented in a biographical manner or style.
  • C. hasBiographicalWork
    Indicates that there exists a biographical work (such as a book, article, or film) whose subject is the given entity.
  • D. hasBiographicalSubjectRole
    Indicates that a role is the biographical subject of a biographical work or account.
  • E. genreOfBiographicalDepiction chosen
    Indicates that one entity is the genre category assigned to a biographical depiction (such as a biographical film, book, or artwork) about another entity.
  • F. None of above.

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_69f348f8ce388190ae84376b1f348f12 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f70e8755a48190931eaa77946f9460 completed May 3, 2026, 8:59 a.m.
PD Predicate disambiguation batch_69f70abc00848190a1c3f495ef6c8dc6 completed May 3, 2026, 8:43 a.m.
Created at: May 1, 2026, 12:15 a.m.