Triple

T14484008
Position Surface form Disambiguated ID Type / Status
Subject Theodora E359181 entity
Predicate relationshipTypeWithEleanorLance P114387 FINISHED
Object ambiguous intimacy and tension 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: ambiguous intimacy and tension | Statement: [Theodora, relationshipTypeWithEleanorLance, ambiguous intimacy and tension]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithEleanorLance
Context triple: [Theodora, relationshipTypeWithEleanorLance, ambiguous intimacy and tension]
  • A. relationshipTypeWithLorraineBroughton
    Indicates the specific nature or category of relationship an entity has with Lorraine Broughton.
  • B. relationshipTypeWithEunice
    Indicates the specific nature or category of the relationship that an entity has with Eunice.
  • C. relationshipTypeWithLizzieEustace
    Indicates the specific nature or category of relationship that an entity has with Lizzie Eustace.
  • D. relationshipToElaineRisley
    Indicates the nature or type of connection an entity has to Elaine Risley, such as familial, social, or professional relationship.
  • E. relationshipTypeWithCeliaCoplestone
    Indicates the specific nature or category of relationship that an entity has with Celia Coplestone.
  • 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_69d8279740308190af9df93a3af8592e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de924d7f4c8190b1f62b5ffe1ff649 completed April 14, 2026, 7:15 p.m.
PD Predicate disambiguation batch_69de5c487b4c819097803e58dca628a5 completed April 14, 2026, 3:24 p.m.
PDg Predicate description generation batch_69de5fb4de14819092acdecbd201d672 completed April 14, 2026, 3:39 p.m.
Created at: April 10, 2026, 1:20 a.m.