Triple

T3315559
Position Surface form Disambiguated ID Type / Status
Subject Tom Buchanan E69672 entity
Predicate relationshipDescription P10690 FINISHED
Object Nick Carraway's acquaintance and cousin-in-law 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: Nick Carraway's acquaintance and cousin-in-law | Statement: [Tom Buchanan, relationshipDescription, Nick Carraway's acquaintance and cousin-in-law]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: relationshipDescription
Context triple: [Tom Buchanan, relationshipDescription, Nick Carraway's acquaintance and cousin-in-law]
  • A. relationshipType chosen
    Indicates the specific kind of relationship that exists between two or more entities.
  • B. relationshipFocus
    Indicates a relationship where particular attention, priority, or emphasis is placed on the connection between two or more entities.
  • C. relationshipDynamic
    Indicates a changing or evolving pattern of interaction between entities, such as shifts in their roles, closeness, or influence over time.
  • D. relationshipToHumans
    Indicates the nature or type of connection, association, or relevance that something has specifically with humans.
  • E. termRelationTo
    Indicates a general relational association between one term and another, without specifying the exact nature of that relationship.
  • 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_69ad85a0bb048190a5458d2738012d61 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb110b28081909b366623e3b0783d completed March 8, 2026, 5:25 p.m.
PD Predicate disambiguation batch_69ada4282730819092aa39c5f9269df0 completed March 8, 2026, 4:30 p.m.
Created at: March 8, 2026, 3:11 p.m.