Triple

T12890912
Position Surface form Disambiguated ID Type / Status
Subject Earl of Snowdon E308360 entity
Predicate associatedWithProfessionOfFirstHolder P35215 FINISHED
Object photographer 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: photographer | Statement: [Earl of Snowdon, associatedWithProfessionOfFirstHolder, photographer]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: associatedWithProfessionOfFirstHolder
Context triple: [Earl of Snowdon, associatedWithProfessionOfFirstHolder, photographer]
  • A. isAssociatedWithProfessionOfBearer chosen
    Indicates that one entity is connected to, or involved with, the profession or occupational role held by another entity.
  • B. occupationOfAssociatedPerson
    Indicates the job or professional role held by a person who is associated with another referenced entity.
  • C. alsoHeldByFirstHolder
    Indicates that something possessed or held by a second holder is (or was) also possessed or held by the first holder.
  • D. leaderAssociatedWith
    Indicates a relationship where a leader is connected or affiliated with a particular entity, such as an organization, group, or cause.
  • E. originallyAssociatedWith
    Indicates that an entity was first linked, connected, or affiliated with another entity before any later changes in association.
  • 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_69d7bdf7c1f0819098102569a8d8cbf5 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d97146d2208190be5ae26e51193b67 completed April 10, 2026, 9:53 p.m.
PD Predicate disambiguation batch_69d96fa776648190b9b5c30722ea50b6 completed April 10, 2026, 9:46 p.m.
Created at: April 9, 2026, 5:39 p.m.