Triple

T11114490
Position Surface form Disambiguated ID Type / Status
Subject Avokaya language E262848 entity
Predicate hasAlternativeName P39 FINISHED
Object Avo
Avo is an alternative name for the Avokaya language, a Central Sudanic language spoken primarily in South Sudan and the Democratic Republic of the Congo.
 E905151 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: Avo | Statement: [Avokaya language, hasAlternativeName, Avo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Avo
Context triple: [Avokaya language, hasAlternativeName, Avo]
  • A. Avoca
    Avoca is a small city located in Pottawattamie County in southwestern Iowa, United States.
  • B. Kakkalos
    Kakkalos is a Greek surname most notably associated with Christos Kakkalos, the first recorded climber to reach the summit of Mount Olympus.
  • C. Rizo
    Rizo is a small settlement within the Municipality of Missolonghi in western Greece.
  • D. Nabo
    Nabo is a diminutive form of the given name Nabil, often used as a familiar or affectionate nickname.
  • E. Ave
    Ave is an intermunicipal subregion in northern Portugal known for its dense urbanization and strong textile and manufacturing industries.
  • 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: Avo
Triple: [Avokaya language, hasAlternativeName, Avo]
Generated description
Avo is an alternative name for the Avokaya language, a Central Sudanic language spoken primarily in South Sudan and the Democratic Republic of the Congo.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Avo
Target entity description: Avo is an alternative name for the Avokaya language, a Central Sudanic language spoken primarily in South Sudan and the Democratic Republic of the Congo.
  • A. Avoca
    Avoca is a small city located in Pottawattamie County in southwestern Iowa, United States.
  • B. Kakkalos
    Kakkalos is a Greek surname most notably associated with Christos Kakkalos, the first recorded climber to reach the summit of Mount Olympus.
  • C. Rizo
    Rizo is a small settlement within the Municipality of Missolonghi in western Greece.
  • D. Nabo
    Nabo is a diminutive form of the given name Nabil, often used as a familiar or affectionate nickname.
  • E. Ave
    Ave is an intermunicipal subregion in northern Portugal known for its dense urbanization and strong textile and manufacturing industries.
  • 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_69d6aa9b46cc8190b19f9f0cc45bf322 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79aa637888190935e852281408356 completed April 9, 2026, 12:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69e42d7da99881908d38ea66c37dfb92 completed April 19, 2026, 1:18 a.m.
NEDg Description generation batch_69e42e67724481908bd9e73487a80d44 completed April 19, 2026, 1:22 a.m.
NED2 Entity disambiguation (via description) batch_69e4308103c48190b32ee3047d9a0860 completed April 19, 2026, 1:31 a.m.
Created at: April 8, 2026, 9:27 p.m.