Triple

T28155793
Position Surface form Disambiguated ID Type / Status
Subject Colonel Faris Al-Ghazi E714742 entity
Predicate investigatesInStory P158202 FINISHED
Object terrorist attack 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: terrorist attack | Statement: [Colonel Faris Al-Ghazi, investigatesInStory, terrorist attack]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: investigatesInStory
Context triple: [Colonel Faris Al-Ghazi, investigatesInStory, terrorist attack]
  • A. investigatesIn chosen
    Indicates that an entity conducts an investigation or inquiry within, or focused on, a particular context, location, or domain.
  • B. portraysInvestigationOf
    Indicates that one entity depicts, represents, or illustrates the process, details, or conduct of an investigation concerning another entity.
  • C. investigatesAt
    Indicates that an entity conducts an investigation or research activity at a specific location or institution.
  • D. investigatedBy
    Indicates that an entity is the subject of an investigation carried out by another entity.
  • E. stakesInStory
    Indicates that one entity has a personal investment, risk, or potential gain/loss tied to the outcome of another entity’s story or narrative.
  • 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_69efd6b156448190bfa15958208395c3 completed April 27, 2026, 9:35 p.m.
NER Named-entity recognition batch_69f65876c52c8190bc889c7a67bd07f3 completed May 2, 2026, 8:03 p.m.
PD Predicate disambiguation batch_69f6575d89788190aca478e4aea05a65 completed May 2, 2026, 7:58 p.m.
Created at: April 27, 2026, 10:02 p.m.