Triple

T14487695
Position Surface form Disambiguated ID Type / Status
Subject Hothouse E359278 entity
Predicate characterOccupationOfLead P21567 FINISHED
Object psychiatrist 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: psychiatrist | Statement: [Hothouse, characterOccupationOfLead, psychiatrist]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: characterOccupationOfLead
Context triple: [Hothouse, characterOccupationOfLead, psychiatrist]
  • A. featuresProtagonistOccupation chosen
    Indicates that the work’s main character has a specified occupation or job role.
  • B. notableCharacterOccupation
    Indicates that a notable character is associated with a specific occupation or professional role.
  • C. leadActorOccupation
    Indicates that the occupation specified is the primary professional role of the lead actor in a given work or context.
  • D. mainCastMemberRole
    Indicates that an entity’s role specifies the character or position they portray as a principal member of a production’s main cast.
  • E. followsCharacterOccupation
    Indicates that one character’s occupation or job role comes after or succeeds another character’s occupation in a sequence or progression.
  • 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_69d8279740308190af9df93a3af8592e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de924ee0f08190baf68318b41fa64d completed April 14, 2026, 7:15 p.m.
PD Predicate disambiguation batch_69de5c487b4c819097803e58dca628a5 completed April 14, 2026, 3:24 p.m.
Created at: April 10, 2026, 1:20 a.m.