Triple

T17056180
Position Surface form Disambiguated ID Type / Status
Subject Dakar Department E413825 entity
Predicate contains P35 FINISHED
Object Ouakam E403472 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: Ouakam | Statement: [Dakar Department, contains, Ouakam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ouakam
Context triple: [Dakar Department, contains, Ouakam]
  • A. Ouakam chosen
    Ouakam is a coastal district of Dakar, Senegal, known for its historic fishing community, military installations, and prominent location beneath the African Renaissance Monument.
  • B. Ogna
    Ogna is a river in Trøndelag county, Norway, known for flowing through the municipality of Steinkjer.
  • C. Olema
    Olema is a small unincorporated community in Marin County, California, known as a gateway to Point Reyes National Seashore and the surrounding coastal countryside.
  • D. Iaru
    Iaru is the ancient Egyptian paradise-like afterlife realm, often depicted as fertile reed fields where the blessed dead live eternally.
  • E. Owaka
    Owaka is a small rural town in New Zealand’s Catlins region, known as a gateway to the area’s rugged coastline and native forests.
  • 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_69d886cde3d481908d4d01ba88ba7eb7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3db7934e881909e9f0ae956fb0816 completed April 18, 2026, 7:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a012346bcfc819093cd922baa94e186 completed May 11, 2026, 12:31 a.m.
Created at: April 10, 2026, 5:34 a.m.