Triple

T8434554
Position Surface form Disambiguated ID Type / Status
Subject Tis Issat E199193 entity
Predicate locatedNear P294 FINISHED
Object Bahir Dar E192971 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: Bahir Dar | Statement: [Tis Issat, locatedNear, Bahir Dar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bahir Dar
Context triple: [Tis Issat, locatedNear, Bahir Dar]
  • A. Bahir Dar chosen
    Bahir Dar is a major city in northwestern Ethiopia, known for its location on the southern shore of Lake Tana and as a gateway to the Blue Nile Falls and nearby monasteries.
  • B. Awasa
    Awasa is a city in southern Ethiopia, known as the capital of the Sidama Region and a hub by Lake Awasa.
  • C. Senafe
    Senafe is a town in southern Eritrea known for its strategic location near the Ethiopian border and its surrounding highland landscapes.
  • D. Mekelle
    Mekelle is the largest city and administrative, economic, and cultural center of Ethiopia’s northern Tigray Region.
  • E. Addis Ababa
    Addis Ababa is the capital and largest city of Ethiopia, serving as a major political and diplomatic hub in Africa that hosts numerous international organizations and institutions.
  • 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_69ca8314cd6c8190a6b8c2a1096e18f3 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbd1a905ac8190b1015e1da9b16938 completed March 31, 2026, 1:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce1d71d9748190903ed97dde6d28f4 completed April 2, 2026, 7:40 a.m.
Created at: March 30, 2026, 6:07 p.m.