Triple

T24479433

Position	Surface form	Disambiguated ID	Type / Status
Subject	Wiawso Sehwi	`E617325`	entity
Predicate	hasAlternativeName	`P39`	FINISHED
Object	Wiawso Sefwi Wiawso Sefwi is a town in the Western North Region of Ghana that serves as a local administrative and commercial center for the surrounding Sefwi area.	`E1637327`	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: Wiawso Sefwi | Statement: [Wiawso Sehwi, hasAlternativeName, Wiawso Sefwi]

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: Wiawso Sefwi
Triple: [Wiawso Sehwi, hasAlternativeName, Wiawso Sefwi]

Generated description

Wiawso Sefwi is a town in the Western North Region of Ghana that serves as a local administrative and commercial center for the surrounding Sefwi area.

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_69e2d7f3ae788190b683394db15f220e`	completed	April 18, 2026, 1:01 a.m.
NER	Named-entity recognition	`batch_69f29ed509c88190a0071f8e78b38887`	completed	April 30, 2026, 12:14 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a0fee768f888190902545ff9e619605`	completed	May 22, 2026, 5:49 a.m.
NEDg	Description generation	`batch_6a0fef537a8c8190ac04651a1b03602b`	completed	May 22, 2026, 5:53 a.m.
NED2	Entity disambiguation (via description)	`batch_6a0ff00803b481908e7315142e3eb396`	completed	May 22, 2026, 5:56 a.m.

Created at: April 18, 2026, 2:21 a.m.