Triple

T11472770
Position Surface form Disambiguated ID Type / Status
Subject Dr. Pimple Popper E271948 entity
Predicate hasMainProfessionOfLead P50979 FINISHED
Object dermatologist 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: dermatologist | Statement: [Dr. Pimple Popper, hasMainProfessionOfLead, dermatologist]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasMainProfessionOfLead
Context triple: [Dr. Pimple Popper, hasMainProfessionOfLead, dermatologist]
  • A. hasMainRole
    Indicates that an entity holds the primary or most significant role in relation to another entity or context.
  • B. hasMainPerformerOccupation chosen
    Indicates that an entity’s primary or main performer is associated with a specified occupation or professional role.
  • C. hasPrimaryDirector
    Indicates that an entity has a specific person or organization serving as its main or lead director.
  • D. isAssociatedWithProfessionOfBearer
    Indicates that one entity is connected to, or involved with, the profession or occupational role held by another entity.
  • E. hasNotableProfessionDistributionIn
    Indicates that the distribution or prevalence of notable professions associated with an entity is observed or characterized within a specified context, such as a location or group.
  • 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_69d6aae0c8d881908a5a360c0be3242e completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8294b3f388190a587c358313f7260 completed April 9, 2026, 10:33 p.m.
PD Predicate disambiguation batch_69d8086ecd6c81908f424864857762d6 completed April 9, 2026, 8:13 p.m.
Created at: April 8, 2026, 9:35 p.m.