Triple

T3554960
Position Surface form Disambiguated ID Type / Status
Subject Nasarawa State E75196 entity
Predicate localGovernmentArea P3379 FINISHED
Object Kokona
Kokona is a local government area in Nasarawa State, Nigeria, serving as an administrative subdivision of the state.
 E368497 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: Kokona | Statement: [Nasarawa State, localGovernmentArea, Kokona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kokona
Context triple: [Nasarawa State, localGovernmentArea, Kokona]
  • A. Kono
    Kono is a Japanese surname most prominently associated with politician Taro Kono, a leading figure in contemporary Japanese politics.
  • B. Kono
    Kono is a major Mande language spoken primarily in parts of West Africa, notably in Sierra Leone and neighboring regions.
  • C. Kuki
    The Kuki are an indigenous ethnic group of Northeast India and surrounding regions, known for their distinct Tibeto-Burman language varieties, clan-based social structure, and rich cultural traditions.
  • D. Konedobu
    Konedobu is a suburb of Port Moresby in Papua New Guinea, known for housing many government offices and administrative facilities.
  • E. Kohat
    Kohat is a historic city in northwestern Pakistan known for its strategic location, military cantonment, and role as a regional administrative and commercial center.
  • 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: Kokona
Triple: [Nasarawa State, localGovernmentArea, Kokona]
Generated description
Kokona is a local government area in Nasarawa State, Nigeria, serving as an administrative subdivision of the state.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kokona
Target entity description: Kokona is a local government area in Nasarawa State, Nigeria, serving as an administrative subdivision of the state.
  • A. Kono
    Kono is a Japanese surname most prominently associated with politician Taro Kono, a leading figure in contemporary Japanese politics.
  • B. Kono
    Kono is a major Mande language spoken primarily in parts of West Africa, notably in Sierra Leone and neighboring regions.
  • C. Kuki
    The Kuki are an indigenous ethnic group of Northeast India and surrounding regions, known for their distinct Tibeto-Burman language varieties, clan-based social structure, and rich cultural traditions.
  • D. Konedobu
    Konedobu is a suburb of Port Moresby in Papua New Guinea, known for housing many government offices and administrative facilities.
  • E. Kohat
    Kohat is a historic city in northwestern Pakistan known for its strategic location, military cantonment, and role as a regional administrative and commercial center.
  • 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_69ad85d45090819086f34fb85d850a1e completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc0569fbc81909b855b6990c1415b completed March 8, 2026, 6:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b38bf1c3e881908e7fc3b4df24e72b completed March 13, 2026, 4 a.m.
NEDg Description generation batch_69b3b33409788190bdb164bef3ae1bd3 completed March 13, 2026, 6:48 a.m.
NED2 Entity disambiguation (via description) batch_69b3b3ade7ac819095f007f053766852 completed March 13, 2026, 6:50 a.m.
Created at: March 8, 2026, 3:20 p.m.