Triple

T15063439
Position Surface form Disambiguated ID Type / Status
Subject Winneba E379693 entity
Predicate hasLanguage P15 FINISHED
Object Effutu language
Effutu language is a Niger-Congo language spoken primarily by the Effutu people in and around the coastal town of Winneba in Ghana.
 E1135034 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: Effutu language | Statement: [Winneba, hasLanguage, Effutu language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Effutu language
Context triple: [Winneba, hasLanguage, Effutu language]
  • A. Bafut language
    The Bafut language is a Grassfields Bantu language spoken primarily by the Bafut people in the Northwest Region of Cameroon.
  • B. Tontemboan language
    The Tontemboan language is an Austronesian language spoken by the Tontemboan people of North Sulawesi, Indonesia, and is one of the traditional Minahasan languages of the region.
  • C. Nyindrou language
    The Nyindrou language is an Oceanic language spoken by communities in the Admiralty Islands of Papua New Guinea.
  • D. Sateré-Mawé language
    The Sateré-Mawé language is an indigenous Tupian language spoken by the Sateré-Mawé people of the Brazilian Amazon.
  • E. Marakwet language
    The Marakwet language is a Southern Nilotic language spoken by the Marakwet people of Kenya and is closely related to other Kalenjin languages such as Kipsigis.
  • 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: Effutu language
Triple: [Winneba, hasLanguage, Effutu language]
Generated description
Effutu language is a Niger-Congo language spoken primarily by the Effutu people in and around the coastal town of Winneba in Ghana.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Effutu language
Target entity description: Effutu language is a Niger-Congo language spoken primarily by the Effutu people in and around the coastal town of Winneba in Ghana.
  • A. Bafut language
    The Bafut language is a Grassfields Bantu language spoken primarily by the Bafut people in the Northwest Region of Cameroon.
  • B. Tontemboan language
    The Tontemboan language is an Austronesian language spoken by the Tontemboan people of North Sulawesi, Indonesia, and is one of the traditional Minahasan languages of the region.
  • C. Nyindrou language
    The Nyindrou language is an Oceanic language spoken by communities in the Admiralty Islands of Papua New Guinea.
  • D. Sateré-Mawé language
    The Sateré-Mawé language is an indigenous Tupian language spoken by the Sateré-Mawé people of the Brazilian Amazon.
  • E. Marakwet language
    The Marakwet language is a Southern Nilotic language spoken by the Marakwet people of Kenya and is closely related to other Kalenjin languages such as Kipsigis.
  • 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_69d85cd7683881908d405c1b5d7b4f7f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69dedee803ac81908bb7d66e49c2eb72 completed April 15, 2026, 12:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69fea5c8b3ac8190b8fc921b6e6eeed5 completed May 9, 2026, 3:11 a.m.
NEDg Description generation batch_69fea74447d481908b290d6be0f0898e completed May 9, 2026, 3:17 a.m.
NED2 Entity disambiguation (via description) batch_69fea81b77708190b0aafcb504dc72d1 completed May 9, 2026, 3:20 a.m.
Created at: April 10, 2026, 3:02 a.m.