Triple

T544015
Position Surface form Disambiguated ID Type / Status
Subject Mauritania E12692 entity
Predicate largestCity P235 FINISHED
Object Nouakchott E13475 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: Nouakchott | Statement: [Mauritania, largestCity, Nouakchott]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nouakchott
Context triple: [Mauritania, largestCity, Nouakchott]
  • A. Nouakchott chosen
    Nouakchott is the capital and largest city of Mauritania, located on the Atlantic coast of Northwest Africa.
  • B. Tadjoura
    Tadjoura is a historic coastal town in Djibouti on the Gulf of Tadjoura, known as one of the country’s oldest settlements and a traditional trading hub.
  • C. Dakar
    Dakar is the capital and largest city of Senegal, located on the Atlantic coast and serving as a major political, economic, and cultural hub of West Africa.
  • D. Bamako
    Bamako is the capital and largest city of Mali, serving as a major political, economic, and cultural center in West Africa.
  • E. Niamey
    Niamey is the capital and largest city of Niger, situated along the Niger River and serving as the country’s political, economic, and cultural center.
  • 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_69a49334226c81908b0ea1689ef6aa3f completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a498dea88881908a938fe8f2313bec completed March 1, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69a51035ebc48190b51f2148cb51a20f completed March 2, 2026, 4:21 a.m.
Created at: March 1, 2026, 7:32 p.m.