Triple

T1709564
Position Surface form Disambiguated ID Type / Status
Subject Senegal E36946 entity
Predicate borderCountry P224 FINISHED
Object Mali E40373 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: Mali | Statement: [Senegal, borderCountry, Mali]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mali
Context triple: [Senegal, borderCountry, Mali]
  • A. Mali chosen
    Mali is a landlocked West African country known for its historic trading cities like Timbuktu, rich Sahelian culture, and significant role in the ancient Mali Empire.
  • B. Burkina Faso
    Burkina Faso is a landlocked West African country known for its diverse cultures, Sahelian landscapes, and capital city, Ouagadougou.
  • C. Mauritania
    Mauritania is a Northwest African country on the Atlantic coast, known for its vast Saharan landscapes, mixed Arab-Berber and Sub-Saharan cultures, and significant iron ore resources.
  • D. Senegal
    Senegal is a West African country on the Atlantic coast known for its vibrant culture, historic role in transatlantic trade, and diverse coastal and Sahelian landscapes.
  • E. Guinea
    Guinea is a West African country on the Atlantic coast known for its rich mineral resources, diverse ethnic groups, and role as a major producer of bauxite.
  • 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_69a88617439c819094ffb5d16a0f6307 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa631329088190a2ce8f755bd69fc7 completed March 6, 2026, 5:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69b511ebd11c8190ba5a6917d3731de9 completed March 14, 2026, 7:44 a.m.
Created at: March 4, 2026, 7:30 p.m.