Triple

T8459807
Position Surface form Disambiguated ID Type / Status
Subject Bale Zone E200011 entity
Predicate contains P35 FINISHED
Object Goba woreda
Goba woreda is an administrative district in Ethiopia’s Oromia Region, known for its highland landscapes and proximity to the Bale Mountains.
 E735307 NE FINISHED

How this triple was built (4 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: Goba woreda | Statement: [Bale Zone, contains, Goba woreda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Goba woreda
Context triple: [Bale Zone, contains, Goba woreda]
  • A. Wadla woreda
    Wadla woreda is an administrative district in Ethiopia's Amhara Region, known for its highland terrain and predominantly agrarian communities.
  • B. Kobo woreda
    Kobo woreda is an administrative district in northern Ethiopia, located in the Amhara Region.
  • C. Meket woreda
    Meket woreda is an administrative district in the Amhara Region of northern Ethiopia, known for its highland terrain and predominantly rural, agrarian communities.
  • D. Gidan woreda
    Gidan woreda is an administrative district in the Amhara Region of northern Ethiopia.
  • E. Lasta woreda
    Lasta woreda is an administrative district in Ethiopia’s Amhara Region that includes the historic town of Lalibela, famous for its rock-hewn churches.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Goba woreda
Triple: [Bale Zone, contains, Goba woreda]
Generated description
Goba woreda is an administrative district in Ethiopia’s Oromia Region, known for its highland landscapes and proximity to the Bale Mountains.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Goba woreda
Target entity description: Goba woreda is an administrative district in Ethiopia’s Oromia Region, known for its highland landscapes and proximity to the Bale Mountains.
  • A. Wadla woreda
    Wadla woreda is an administrative district in Ethiopia's Amhara Region, known for its highland terrain and predominantly agrarian communities.
  • B. Kobo woreda
    Kobo woreda is an administrative district in northern Ethiopia, located in the Amhara Region.
  • C. Meket woreda
    Meket woreda is an administrative district in the Amhara Region of northern Ethiopia, known for its highland terrain and predominantly rural, agrarian communities.
  • D. Gidan woreda
    Gidan woreda is an administrative district in the Amhara Region of northern Ethiopia.
  • E. Lasta woreda
    Lasta woreda is an administrative district in Ethiopia’s Amhara Region that includes the historic town of Lalibela, famous for its rock-hewn churches.
  • F. None of above. chosen

Provenance (5 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_69ca83198c4c8190a337bf717d1813f5 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe49fca788190a8728ff74f4d26f5 completed March 31, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce1df214ac8190b59daa88e3a930bc completed April 2, 2026, 7:42 a.m.
NEDg Description generation batch_69ce21c53298819080137c87ff487b50 completed April 2, 2026, 7:59 a.m.
NED2 Entity disambiguation (via description) batch_69ce23d6da1c8190a28bc895d737595e completed April 2, 2026, 8:07 a.m.
Created at: March 30, 2026, 6:10 p.m.