Triple

T929842
Position Surface form Disambiguated ID Type / Status
Subject Red Cross emblem E20064 entity
Predicate protectiveUseMeaning P1040 FINISHED
Object grants special protection to medical services — 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: grants special protection to medical services | Statement: [Red Cross emblem, protectiveUseMeaning, grants special protection to medical services]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: protectiveUseMeaning
Context triple: [Red Cross emblem, protectiveUseMeaning, grants special protection to medical services]
  • A. aimsToProtect
    Indicates an intention or purpose to safeguard or defend one entity, value, or condition from harm, risk, or undesirable outcomes.
  • B. protects chosen
    Indicates taking action to keep someone or something safe from harm, danger, or negative effects.
  • C. providesProtectionAgainst
    Indicates that one entity serves to guard, shield, or defend another entity from a specified harm, threat, or adverse effect.
  • D. protectionObjective
    Indicates that one entity has the goal or purpose of safeguarding, defending, or preserving another entity or its interests.
  • E. reasonForUse
    Indicates that one entity specifies the justification, purpose, or motivation for using another entity.
  • 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_69a493af3dc48190adb7263e6e445ea1 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b349b3d0819090c58b4fb60c6a1b completed March 1, 2026, 9:44 p.m.
PD Predicate disambiguation batch_69a4b29876348190a29f4ff9878074a5 completed March 1, 2026, 9:41 p.m.
Created at: March 1, 2026, 7:40 p.m.