Triple

T4496118
Position Surface form Disambiguated ID Type / Status
Subject Battle of Konna E100699 entity
Predicate place P373 FINISHED
Object Konna
Konna is a town in central Mali that gained prominence as a strategic battleground during the 2013 conflict between Malian and Islamist forces.
E446305 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: Konna | Statement: [Battle of Konna, place, Konna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Konna
Context triple: [Battle of Konna, place, Konna]
  • 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. Kokona
    Kokona is a local government area in Nasarawa State, Nigeria, serving as an administrative subdivision of the state.
  • D. Anao
    Anao is a small agricultural municipality located in the province of Tarlac in the Philippines.
  • E. Konedobu
    Konedobu is a suburb of Port Moresby in Papua New Guinea, known for housing many government offices and administrative facilities.
  • 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: Konna
Triple: [Battle of Konna, place, Konna]
Generated description
Konna is a town in central Mali that gained prominence as a strategic battleground during the 2013 conflict between Malian and Islamist forces.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Konna
Target entity description: Konna is a town in central Mali that gained prominence as a strategic battleground during the 2013 conflict between Malian and Islamist forces.
  • 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. Kokona
    Kokona is a local government area in Nasarawa State, Nigeria, serving as an administrative subdivision of the state.
  • D. Anao
    Anao is a small agricultural municipality located in the province of Tarlac in the Philippines.
  • E. Konedobu
    Konedobu is a suburb of Port Moresby in Papua New Guinea, known for housing many government offices and administrative facilities.
  • 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_69bd43cdf15081909a4fa2585ff63b3e completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd56bde14c819091d42839a46291d0 completed March 20, 2026, 2:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd67bfb4788190b64975b1999a8d1e completed March 20, 2026, 3:29 p.m.
NEDg Description generation batch_69bd68503f1c81909742bcf0ac356e52 completed March 20, 2026, 3:31 p.m.
NED2 Entity disambiguation (via description) batch_69bd68b4681c8190abb170ccb054cd05 completed March 20, 2026, 3:33 p.m.
Created at: March 20, 2026, 1 p.m.