Triple

T34795313
Position Surface form Disambiguated ID Type / Status
Subject Sir Clifford Chatterley E1003060 entity
Predicate emotionalRelationshipTo P181894 FINISHED
Object distant from his wife 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: distant from his wife | Statement: [Sir Clifford Chatterley, emotionalRelationshipTo, distant from his wife]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: emotionalRelationshipTo
Context triple: [Sir Clifford Chatterley, emotionalRelationshipTo, distant from his wife]
  • A. emotionallyAttachedTo
    Indicates that one entity has a strong emotional bond, affection, or dependence directed toward another entity.
  • B. emotionalFocusOf
    Indicates that one entity is the primary target or center of another entity’s emotions or emotional attention.
  • C. relationshipToHeed
    Indicates a relationship in which one entity is expected to pay attention to, respect, or follow the guidance, warnings, or wishes of another entity.
  • D. relationshipImpact
    Indicates how one entity’s relationship with another affects or changes those entities or their interaction.
  • E. basisOfRelationship
    Indicates that one entity serves as the foundational reason, cause, or justification for the relationship that exists between two or more entities.
  • 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_69f76db543808190b188c6c86a91491b completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f782f4f10081908f97f6d0d2dbeec7 completed May 3, 2026, 5:16 p.m.
PD Predicate disambiguation batch_69f780ff71cc8190a67e71076fbad81a completed May 3, 2026, 5:08 p.m.
PDg Predicate description generation batch_69f782f416c081908bdd9b1ad456f0e2 completed May 3, 2026, 5:16 p.m.
Created at: May 3, 2026, 3:59 p.m.