Triple

T18365817
Position Surface form Disambiguated ID Type / Status
Subject محافظة الجهراء E440042 entity
Predicate borders P224 FINISHED
Object محافظة العاصمة 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: محافظة العاصمة | Statement: [محافظة الجهراء, borders, محافظة العاصمة]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: محافظة العاصمة
Context triple: [محافظة الجهراء, borders, محافظة العاصمة]
  • A. أمانة العاصمة chosen
    أمانة العاصمة هي محافظة يمنية تضم مدينة صنعاء وتعد المركز الإداري والسياسي الرئيسي في البلاد.
  • B. Madinaty
    Madinaty is a large, modern planned city and residential community on the outskirts of Cairo, Egypt, featuring extensive housing, green spaces, and amenities.
  • C. Qaha Markaz
    Qaha Markaz is an administrative district in Egypt centered around the town of Qaha in the Qalyubia Governorate.
  • D. Kairana
    Kairana is a town and parliamentary constituency in the Shamli district of Uttar Pradesh, India, known for its agrarian population and political significance in north Indian politics.
  • E. Zaria
    Zaria is a historic city in northern Nigeria known as an important center of Hausa culture, Islamic scholarship, and trade.
  • 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_69d8b918221c8190a9f7b563d64ac677 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e5174d31608190851a5bab6878c203 completed April 19, 2026, 5:56 p.m.
Created at: April 10, 2026, 10:38 a.m.