Triple

T37039724
Position Surface form Disambiguated ID Type / Status
Subject Lunda Sul Province E916745 entity
Predicate capital P234 FINISHED
Object Saurimo
Saurimo is a city in northeastern Angola that serves as an important regional center for administration, trade, and transportation.
E2235126 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: Saurimo | Statement: [Lunda Sul Province, capital, Saurimo]
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: Saurimo
Triple: [Lunda Sul Province, capital, Saurimo]
Generated description
Saurimo is a city in northeastern Angola that serves as an important regional center for administration, trade, and transportation.

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_69f76e93ec4c8190be81cf87354d9155 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb58fa6dfc81909813d1a50f47ca3c completed May 6, 2026, 3:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40a7d8674081908c7d611cb1d4704f completed June 28, 2026, 4:49 a.m.
NEDg Description generation batch_6a40aa2c0e008190a87a33d0ce144807 completed June 28, 2026, 4:59 a.m.
NED2 Entity disambiguation (via description) batch_6a40ab4452e08190a170a8dc3bd70550 completed June 28, 2026, 5:04 a.m.
Created at: May 3, 2026, 4:14 p.m.