Triple

T12002526
Position Surface form Disambiguated ID Type / Status
Subject Lango people E285699 entity
Predicate administrativeRegion P285 FINISHED
Object Oyam District E956621 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: Oyam District | Statement: [Lango people, administrativeRegion, Oyam District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oyam District
Context triple: [Lango people, administrativeRegion, Oyam District]
  • A. Oyam District chosen
    Oyam District is an administrative district in northern Uganda known for its predominantly rural communities and agriculture-based economy.
  • B. Ouhai District
    Ouhai District is an urban district of Wenzhou in Zhejiang Province, China, known for its mix of industrial development, residential areas, and scenic mountainous landscapes.
  • C. Shinkay District
    Shinkay District is an administrative district located in Zabul Province in southern Afghanistan.
  • D. Ivanava District
    Ivanava District is an administrative district in the Brest Region of southwestern Belarus, known for its rural settlements and small towns such as Motal.
  • E. Hama District
    Hama District is an administrative district in central Syria that encompasses the city of Hama and surrounding areas within the Hama Governorate.
  • 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_69d6ab45a368819084fce08bf0dc3705 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903c36b248190b446b17def94885b completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f49d259f7c81908366e7d9e61a6c73 completed May 1, 2026, 12:31 p.m.
Created at: April 8, 2026, 9:46 p.m.