Triple

T28152950
Position Surface form Disambiguated ID Type / Status
Subject Sakumono E714669 entity
Predicate partOfUrbanArea P294 FINISHED
Object Greater Accra Metropolitan Area
The Greater Accra Metropolitan Area is the densely populated urban agglomeration centered on Ghana’s capital, Accra, encompassing its surrounding municipalities and suburbs.
E34472 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: Greater Accra Metropolitan Area | Statement: [Sakumono, partOfUrbanArea, Greater Accra Metropolitan Area]
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: Greater Accra Metropolitan Area
Triple: [Sakumono, partOfUrbanArea, Greater Accra Metropolitan Area]
Generated description
The Greater Accra Metropolitan Area is the densely populated urban agglomeration centered on Ghana’s capital, Accra, encompassing its surrounding municipalities and suburbs.

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_69efd6b033208190bf74f80a147e2092 completed April 27, 2026, 9:35 p.m.
NER Named-entity recognition batch_69f641789c90819081eb1c857d032025 completed May 2, 2026, 6:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1632e5b8c08190a95155bb044f13d1 completed May 26, 2026, 11:55 p.m.
NEDg Description generation batch_6a1633a0bd1881908757c68e04bdc509 completed May 26, 2026, 11:58 p.m.
NED2 Entity disambiguation (via description) batch_6a1634122f8c8190af25b6651fd12796 completed May 27, 2026, midnight
Created at: April 27, 2026, 10 p.m.