Triple

T349400
Position Surface form Disambiguated ID Type / Status
Subject Morocco E7408 entity
Predicate capital P234 FINISHED
Object Rabat E8849 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: Rabat | Statement: [Morocco, capital, Rabat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rabat
Context triple: [Morocco, capital, Rabat]
  • A. Rabat chosen
    Rabat is the capital city of Morocco, located on the Atlantic coast and known for its historic medina, coastal fortifications, and role as a political and administrative center.
  • B. Marrakesh
    Marrakesh is a historic and vibrant city in western Morocco, renowned for its bustling medina, iconic red sandstone architecture, and rich cultural heritage.
  • C. Tunis
    Tunis is the capital and largest city of Tunisia, serving as a major political, economic, and cultural center in the Arab world.
  • D. Algiers
    Algiers is the capital and largest city of Algeria, a major political, economic, and cultural center on the Mediterranean coast of North Africa.
  • E. Kairouan
    Kairouan is an ancient Islamic city in central Tunisia renowned for its historic mosques, traditional architecture, and status as a major center of early Muslim scholarship and pilgrimage.
  • 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_69a2e7e696948190bebc966535995e45 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2eb1dc5f88190b54d084c6def7fc5 completed Feb. 28, 2026, 1:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3e0165b6481909345301df3f2144d completed March 1, 2026, 6:43 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.