Triple

T35320986
Position Surface form Disambiguated ID Type / Status
Subject Uganda National Roads Network E1020037 entity
Predicate hasComponent P35 FINISHED
Object Gulu–Nimule Road
Gulu–Nimule Road is a major highway in northern Uganda that connects the city of Gulu to the South Sudan border at Nimule, serving as a key regional trade and transport corridor.
E2152389 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: Gulu–Nimule Road | Statement: [Uganda National Roads Network, hasComponent, Gulu–Nimule Road]
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: Gulu–Nimule Road
Triple: [Uganda National Roads Network, hasComponent, Gulu–Nimule Road]
Generated description
Gulu–Nimule Road is a major highway in northern Uganda that connects the city of Gulu to the South Sudan border at Nimule, serving as a key regional trade and transport corridor.

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_69f76de9d45c81908a2ed0956b448b65 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f79099b9508190934ec3469af1f827 completed May 3, 2026, 6:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a387cf6a1ec8190be8c46edb098845c completed June 22, 2026, 12:08 a.m.
NEDg Description generation batch_6a387d8bebac8190945e3bd73b0e9222 completed June 22, 2026, 12:10 a.m.
NED2 Entity disambiguation (via description) batch_6a387dfd11588190b56499799b37f578 completed June 22, 2026, 12:12 a.m.
Created at: May 3, 2026, 4:03 p.m.