Triple

T16428322
Position Surface form Disambiguated ID Type / Status
Subject Northern Gurage E399002 entity
Predicate hasLanguageBranch P1967 FINISHED
Object Muher E1119786 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: Muher | Statement: [Northern Gurage, hasLanguageBranch, Muher]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Muher
Context triple: [Northern Gurage, hasLanguageBranch, Muher]
  • A. Muher chosen
    Muher is a Gurage language variety spoken in Ethiopia, known as one of the dialects of the Sebat Bet Gurage cluster within the Ethiosemitic language family.
  • B. Muhu
    Muhu is a large Estonian island in the Baltic Sea known for its traditional villages, distinctive folk culture, and role as a gateway between the mainland and Saaremaa.
  • C. Mahur
    Mahur is a small town in the Dima Hasao district of Assam, India, known as a local commercial and transport hub in the region’s hilly terrain.
  • D. Mahur
    Mahur is a small settlement located in the Lihir Islands of Papua New Guinea, known for its remote island community and proximity to major gold mining operations.
  • E. Mugatu
    Mugatu is the flamboyant, villainous fashion designer portrayed by Will Ferrell in the comedy film "Zoolander."
  • 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_69d87f2b9024819085c20e52de95d583 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e328fc223c8190bbed29907351a6f6 completed April 18, 2026, 6:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00458331748190a4bd1c5d2d466e6d completed May 10, 2026, 8:44 a.m.
Created at: April 10, 2026, 5:09 a.m.