Triple

T8879845
Position Surface form Disambiguated ID Type / Status
Subject محمد البرادعي E211380 entity
Predicate residence P75 FINISHED
Object القاهرة E3705 NE 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: القاهرة | Statement: [محمد البرادعي, residence, القاهرة]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: القاهرة
Context triple: [محمد البرادعي, residence, القاهرة]
  • A. Cairo chosen
    Cairo is the capital and largest city of Egypt, a historic metropolis on the Nile renowned for its rich Islamic heritage and proximity to the ancient pyramids.
  • B. Cairo
    Cairo is a 2D graphics library that provides high-quality vector-based drawing capabilities for multiple output devices and backends.
  • C. Cairo
    Cairo is a 2D graphics library that provides high-quality vector-based drawing with support for multiple output backends such as image buffers, PDF, and SVG.
  • D. Alexandria, Egypt
    Alexandria, Egypt is a historic Mediterranean port city founded by Alexander the Great, renowned for its ancient library, lighthouse, and enduring cultural significance in Egypt.
  • E. New Cairo
    New Cairo is a planned satellite city east of central Cairo in Egypt, developed to ease congestion in the capital and host modern residential, educational, and business districts.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69ca838f9e20819096ab1f236a70381a completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc61677c9c8190aa09dc2a05d4cf95 completed April 1, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfeb1d130c81909f7f23b7ad8bba9f completed April 3, 2026, 4:30 p.m.
Created at: March 30, 2026, 6:52 p.m.