Triple

T34527410
Position Surface form Disambiguated ID Type / Status
Subject John Pendleton E886435 entity
Predicate relationshipTypeWithPollyanna Whittier P205459 FINISHED
Object benefactor 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: benefactor | Statement: [John Pendleton, relationshipTypeWithPollyanna Whittier, benefactor]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithPollyanna Whittier
Context triple: [John Pendleton, relationshipTypeWithPollyanna Whittier, benefactor]
  • A. relationshipToHollyGolightly
    Indicates the nature or type of relationship an entity has with Holly Golightly.
  • B. relationshipTypeWith Dolly Talbo
    Indicates the specific nature or category of the relationship that an entity has with Dolly Talbo.
  • C. relationshipToPolinaAlexandrovna
    Indicates the specific type of personal or social relationship that one entity has with Polina Alexandrovna.
  • D. hasRelationshipTypeWithRoryGilmore
    Indicates that an entity has a specific type of interpersonal relationship or connection with Rory Gilmore.
  • E. relationshipTypeWithKatnissEverdeen
    Indicates the type or nature of the relationship an entity has with Katniss Everdeen.
  • F. None of above. chosen

Provenance (4 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_69f349cd7c148190aa99192b126d1527 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_6a037c92f03c8190ae2751270b195423 completed May 12, 2026, 7:16 p.m.
PD Predicate disambiguation batch_6a0379fbe4a08190bfe65ebd141164e9 completed May 12, 2026, 7:05 p.m.
PDg Predicate description generation batch_6a037c80ba448190853011097a151b7e completed May 12, 2026, 7:16 p.m.
Created at: May 1, 2026, 2:02 a.m.