Triple

T23554739
Position Surface form Disambiguated ID Type / Status
Subject Dokki E578152 entity
Predicate locatedInMetropolitanArea P294 FINISHED
Object Greater Cairo NE NERFINISHED

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: Greater Cairo | Statement: [Dokki, locatedInMetropolitanArea, Greater Cairo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Greater Cairo
Context triple: [Dokki, locatedInMetropolitanArea, Greater Cairo]
  • A. Greater Cairo chosen
    Greater Cairo is Egypt’s largest metropolitan region, encompassing Cairo and its surrounding urban areas as the country’s primary political, economic, and cultural hub.
  • B. Nasr City
    Nasr City is a large, modern district in eastern Cairo known for its wide avenues, residential neighborhoods, commercial centers, and several major governmental and military landmarks.
  • C. Cairo east bank
    Cairo east bank is the main urban side of Egypt’s capital city, hosting many of Cairo’s historic districts, government institutions, and dense residential neighborhoods along the eastern shore of the Nile.
  • D. Cairo
    Cairo is a 2D graphics library that provides high-quality vector-based drawing capabilities for multiple output devices and backends.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245fa93448190919cb04534560542 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1aed253788190ba75109af0e91b37 completed April 29, 2026, 7:10 a.m.
Created at: April 17, 2026, 6:12 p.m.