Triple

T31767932
Position Surface form Disambiguated ID Type / Status
Subject West Nile sub-region E810858 entity
Predicate containsAdministrativeUnit P3892 FINISHED
Object Maracha District
Maracha District is an administrative district in northwestern Uganda, located within the West Nile sub-region and known for its predominantly rural communities and agricultural economy.
E2013804 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: Maracha District | Statement: [West Nile sub-region, containsAdministrativeUnit, Maracha District]
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: Maracha District
Triple: [West Nile sub-region, containsAdministrativeUnit, Maracha District]
Generated description
Maracha District is an administrative district in northwestern Uganda, located within the West Nile sub-region and known for its predominantly rural communities and agricultural economy.

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_69f348e463e08190b902d4819195e1f0 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6abad1ce881909ec57cd74a97cca2 completed May 3, 2026, 1:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3485e8ce748190ae2623cdd2e9a7a4 completed June 18, 2026, 11:57 p.m.
NEDg Description generation batch_6a34875b66608190bbe006cf51c2e2c3 completed June 19, 2026, 12:03 a.m.
NED2 Entity disambiguation (via description) batch_6a3487bf3eb88190bc41cbcf4f7cc24a completed June 19, 2026, 12:05 a.m.
Created at: April 30, 2026, 11:32 p.m.