Triple

T5088201
Position Surface form Disambiguated ID Type / Status
Subject Tanganyika E114687 entity
Predicate hasProtectionConcern P25437 FINISHED
Object attacks on villages 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: attacks on villages | Statement: [Tanganyika, hasProtectionConcern, attacks on villages]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasProtectionConcern
Context triple: [Tanganyika, hasProtectionConcern, attacks on villages]
  • A. isProtectedFor
    Indicates that one entity is safeguarded or preserved specifically for the benefit, use, or rights of another entity.
  • B. hasSecurityConsideration chosen
    Indicates that there is a relevant security-related issue, risk, or precaution associated with the referenced entity.
  • C. isProtectedFrom
    Indicates that one entity is safeguarded or shielded against harm, damage, or adverse effects caused by another entity or factor.
  • D. isProtectedBy
    Indicates that one entity provides protection, defense, or safeguarding for another entity.
  • E. providesProtectionAgainst
    Indicates that one entity serves to guard, shield, or defend another entity from a specified harm, threat, or adverse effect.
  • 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_69bd443e941881908eb4e8c685b6f656 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd75219a94819094fc54c1df448470 completed March 20, 2026, 4:26 p.m.
PD Predicate disambiguation batch_69bd7159adc881909effd4382c395c66 completed March 20, 2026, 4:10 p.m.
Created at: March 20, 2026, 1:40 p.m.