Triple

T9122948
Position Surface form Disambiguated ID Type / Status
Subject Rahmat E218899 entity
Predicate targetAudienceImpact P62009 FINISHED
Object evokes empathy for migrants and outsiders 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: evokes empathy for migrants and outsiders | Statement: [Rahmat, targetAudienceImpact, evokes empathy for migrants and outsiders]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: targetAudienceImpact
Context triple: [Rahmat, targetAudienceImpact, evokes empathy for migrants and outsiders]
  • A. targetMarket
    Indicates the group of consumers or organizations that a product, service, or campaign is specifically intended and designed to reach.
  • B. relatesToAudience chosen
    Indicates a general relationship or relevance between something and a particular audience or group of recipients.
  • C. recognizesImpactOn
    Indicates that one entity acknowledges or understands the effect or consequences it has on another entity or situation.
  • D. typicalAudience
    Indicates the group of people for whom something (such as a work, product, or resource) is primarily intended or most suitable.
  • E. encodingImpact
    Indicates how one encoding or encoding choice affects, modifies, or constrains another process, representation, or outcome.
  • 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_69ca83dddd548190983b96c664f7f367 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca8b5fa188190be6465e74cf26915 completed April 1, 2026, 5:10 a.m.
PD Predicate disambiguation batch_69cc66003e3c819091e1e42c9cf7c781 completed April 1, 2026, 12:25 a.m.
Created at: March 30, 2026, 7:17 p.m.