Triple

T10877330
Position Surface form Disambiguated ID Type / Status
Subject Anne Brontë E256832 entity
Predicate hasOccupationExperience P17879 FINISHED
Object governess in various households 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: governess in various households | Statement: [Anne Brontë, hasOccupationExperience, governess in various households]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasOccupationExperience
Context triple: [Anne Brontë, hasOccupationExperience, governess in various households]
  • A. hasGlobalExperience
    Indicates that an entity possesses experience gained from working, operating, or engaging across multiple countries or international contexts.
  • B. hasWorkedIn chosen
    Indicates that a person has been employed or has performed work within a particular organization, location, or domain for some period of time.
  • C. typeOfExperience
    Indicates that one entity specifies the category or nature of an experience associated with another entity.
  • D. experienceType
    Indicates the specific kind or category of experience associated with an entity or event.
  • E. recommendedExperience
    Indicates that a certain level or type of prior experience is advised or preferred for engaging in the related activity, role, or item.
  • 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_69d6aa848804819081b2713ca0bedf06 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d751ad8cdc819093eafaf12fc23b15 completed April 9, 2026, 7:13 a.m.
PD Predicate disambiguation batch_69d70d360c388190a3d829fe8862434f completed April 9, 2026, 2:21 a.m.
Created at: April 8, 2026, 9:21 p.m.