Triple

T4131920
Position Surface form Disambiguated ID Type / Status
Subject Guéckédou Prefecture E85059 entity
Predicate capital P234 FINISHED
Object Guéckédou
Guéckédou is a town in southern Guinea known as a regional trading center near the borders with Sierra Leone and Liberia.
 E414775 NE FINISHED

How this triple was built (4 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: Guéckédou | Statement: [Guéckédou Prefecture, capital, Guéckédou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Guéckédou
Context triple: [Guéckédou Prefecture, capital, Guéckédou]
  • A. Daloa
    Daloa is a major inland city in western Côte d'Ivoire known as an important commercial and agricultural center, particularly for cocoa production.
  • B. Sikasso
    Sikasso is a major city in southern Mali known as an important agricultural and commercial center near the borders with Burkina Faso and Côte d'Ivoire.
  • C. Koudougou
    Koudougou is a major city in central Burkina Faso known as an important commercial and transportation hub.
  • D. Koulikoro
    Koulikoro is a town and region in southwestern Mali, situated along the Niger River and serving as an important administrative and transport hub.
  • E. Ségou
    Ségou is a historic city in central Mali known for its role as a former Bambara kingdom capital, its Niger River location, and its rich cultural and artistic heritage.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Guéckédou
Triple: [Guéckédou Prefecture, capital, Guéckédou]
Generated description
Guéckédou is a town in southern Guinea known as a regional trading center near the borders with Sierra Leone and Liberia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Guéckédou
Target entity description: Guéckédou is a town in southern Guinea known as a regional trading center near the borders with Sierra Leone and Liberia.
  • A. Daloa
    Daloa is a major inland city in western Côte d'Ivoire known as an important commercial and agricultural center, particularly for cocoa production.
  • B. Sikasso
    Sikasso is a major city in southern Mali known as an important agricultural and commercial center near the borders with Burkina Faso and Côte d'Ivoire.
  • C. Koudougou
    Koudougou is a major city in central Burkina Faso known as an important commercial and transportation hub.
  • D. Koulikoro
    Koulikoro is a town and region in southwestern Mali, situated along the Niger River and serving as an important administrative and transport hub.
  • E. Ségou
    Ségou is a historic city in central Mali known for its role as a former Bambara kingdom capital, its Niger River location, and its rich cultural and artistic heritage.
  • F. None of above. chosen

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_69aed935ccd881909dc61f81bcdb7a78 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af022f55fc81909f2a1a04d0ea59e6 completed March 9, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69b576c26d4c81909b8be74855cbd03f completed March 14, 2026, 2:54 p.m.
NEDg Description generation batch_69b577c2b784819096d8218dd1c1478d completed March 14, 2026, 2:59 p.m.
NED2 Entity disambiguation (via description) batch_69b5782cc448819080e306952da24ac0 completed March 14, 2026, 3:01 p.m.
Created at: March 9, 2026, 3:42 p.m.