Triple

T18375646
Position Surface form Disambiguated ID Type / Status
Subject central Mali E446306 entity
Predicate hasTown P847 FINISHED
Object Djenné 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: Djenné | Statement: [central Mali, hasTown, Djenné]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Djenné
Context triple: [central Mali, hasTown, Djenné]
  • A. Djenné chosen
    Djenné is an ancient Malian town renowned for its mud-brick architecture and historic Great Mosque, a UNESCO World Heritage site and one of the most famous examples of Sudano-Sahelian architecture.
  • B. Djenné Songhay
    Djenné Songhay is a regional variety of the Songhay language spoken around the town of Djenné in Mali.
  • C. Mopti
    Mopti is a major city in central Mali known as a bustling river port and commercial hub situated at the confluence of the Niger and Bani rivers.
  • D. Ségou
    Ségou is a historic city in central Mali known for its role as a former Bambara kingdom capital, its Niger River location, and its rich cultural and artistic heritage.
  • E. Bignona
    Bignona is a town in southern Senegal’s Casamance region, known as a local center of trade and cultural diversity.
  • 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_69d8b9f370b88190b1e5081c2c238e7f completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e51759353481908aa2de599fd2cf3b completed April 19, 2026, 5:56 p.m.
Created at: April 10, 2026, 10:45 a.m.