Triple

T4685034
Position Surface form Disambiguated ID Type / Status
Subject Ruby (character in "Ruby, Don’t Take Your Love to Town") E103899 entity
Predicate spouseInjuryContext P59006 FINISHED
Object war-related injuries 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: war-related injuries | Statement: [Ruby (character in "Ruby, Don’t Take Your Love to Town"), spouseInjuryContext, war-related injuries]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: spouseInjuryContext
Context triple: [Ruby (character in "Ruby, Don’t Take Your Love to Town"), spouseInjuryContext, war-related injuries]
  • A. spouseInvolvedIn
    Indicates that a person's spouse participates in, is associated with, or plays a role in a specified activity, event, or situation.
  • B. spouseDeathContext
    Indicates the circumstances or contextual details surrounding the death of a person’s spouse.
  • C. spouseAction
    Indicates that one person performs an action toward or on their spouse within the context of a marital relationship.
  • D. spouse
    Indicates that two entities are married to each other in a legally or socially recognized partnership.
  • E. spouseExecutionContext
    Indicates that one entity is the spouse of another within a specific legal, temporal, or situational context in which that marital relationship is recognized or relevant.
  • 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_69bd43debbf08190b4bc372e286ec234 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd67c9c3c08190a6c4944cdd1362a8 completed March 20, 2026, 3:29 p.m.
PD Predicate disambiguation batch_69bd6217e0088190836570522e324dc6 completed March 20, 2026, 3:04 p.m.
PDg Predicate description generation batch_69bd67c895dc8190ba648002ff54424b completed March 20, 2026, 3:29 p.m.
Created at: March 20, 2026, 1:16 p.m.