Triple

T10048110
Position Surface form Disambiguated ID Type / Status
Subject Koka Reservoir E207668 entity
Predicate nearCity P350 FINISHED
Object Adama E762155 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: Adama | Statement: [Koka Reservoir, nearCity, Adama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Adama
Context triple: [Koka Reservoir, nearCity, Adama]
  • A. Adama chosen
    Adama is a major Ethiopian city in the Oromia Region, known as an important commercial and transportation hub southeast of Addis Ababa.
  • B. Xala
    Xala is a 1974 satirical film (and earlier novel) by Ousmane Sembène that critiques post-independence African elites through the story of a corrupt businessman afflicted with impotence.
  • C. Djiba
    Djiba is a locality in the Ituri region of the Democratic Republic of the Congo, known as the birthplace of militia leader Thomas Lubanga Dyilo.
  • D. Sikasso
    Sikasso is a major city in southern Mali known as an important agricultural and commercial center near the borders with Burkina Faso and Côte d'Ivoire.
  • E. Kaolack
    Kaolack is a major city in western Senegal known as a regional commercial hub and center of peanut trade.
  • 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_69ca835ad0608190b7c80b292da004f5 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcf8cf4f0819084d831e1986790be completed April 2, 2026, 2:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2828f3980819083d041f09e63d8e6 completed April 5, 2026, 3:41 p.m.
Created at: March 30, 2026, 8:56 p.m.