Triple

T9151774
Position Surface form Disambiguated ID Type / Status
Subject Duchess of Leeds E219602 entity
Predicate inceptionRelation P87041 FINISHED
Object created in connection with the creation of the Duke of Leeds 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: created in connection with the creation of the Duke of Leeds | Statement: [Duchess of Leeds, inceptionRelation, created in connection with the creation of the Duke of Leeds]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: inceptionRelation
Context triple: [Duchess of Leeds, inceptionRelation, created in connection with the creation of the Duke of Leeds]
  • A. semanticRelation
    Indicates a general meaning-based connection between two entities, such as similarity, implication, or conceptual association.
  • B. inRelationshipWith
    Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
  • C. subjectRelation
    Indicates that one entity stands in a specified relational role or connection to another entity.
  • D. showsRelationshipWith
    Indicates that one entity visually or explicitly presents or demonstrates its connection or association with another entity.
  • E. termRelationTo
    Indicates a general relational association between one term and another, without specifying the exact nature of that relationship.
  • 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_69ca83e25418819093c6503deeaf30de completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca96cf4548190a3a45172f0e9d0ec completed April 1, 2026, 5:13 a.m.
PD Predicate disambiguation batch_69cc6603ce8c8190bf6e8d6754bdec54 completed April 1, 2026, 12:25 a.m.
PDg Predicate description generation batch_69cc6a3d230881909635b2ccea35cedb completed April 1, 2026, 12:43 a.m.
Created at: March 30, 2026, 7:20 p.m.