Triple

T11114573
Position Surface form Disambiguated ID Type / Status
Subject Keliko language E262850 entity
Predicate hasAlternativeName P39 FINISHED
Object Kaliko
Kaliko is an alternative name for the Keliko language, a Central Sudanic language spoken by the Keliko people of South Sudan and neighboring regions.
 E905159 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: Kaliko | Statement: [Keliko language, hasAlternativeName, Kaliko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kaliko
Context triple: [Keliko language, hasAlternativeName, Kaliko]
  • A. Maleka
    Maleka is a feminine given name, typically considered a variant spelling of Malika and used in various cultures.
  • B. Kakarla
    Kakarla is an Indian surname notably associated with the renowned Carnatic composer Tyagaraja (Kakarla Tyagabrahmam).
  • C. Katisha
    Katisha is a formidable, older noblewoman and comic villainess in Gilbert and Sullivan’s operetta "The Mikado," known for her dramatic presence and unrequited love for Nanki-Poo.
  • D. Kaula
    Kaula is a small, uninhabited rocky islet off the coast of Kauai in Hawaii, known for its steep cliffs, seabird colonies, and use as a U.S. Navy bombing range.
  • E. Kalomo
    Kalomo is a town in southern Zambia that serves as an important local commercial and administrative center for the surrounding agricultural region.
  • 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: Kaliko
Triple: [Keliko language, hasAlternativeName, Kaliko]
Generated description
Kaliko is an alternative name for the Keliko language, a Central Sudanic language spoken by the Keliko people of South Sudan and neighboring regions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kaliko
Target entity description: Kaliko is an alternative name for the Keliko language, a Central Sudanic language spoken by the Keliko people of South Sudan and neighboring regions.
  • A. Maleka
    Maleka is a feminine given name, typically considered a variant spelling of Malika and used in various cultures.
  • B. Kakarla
    Kakarla is an Indian surname notably associated with the renowned Carnatic composer Tyagaraja (Kakarla Tyagabrahmam).
  • C. Katisha
    Katisha is a formidable, older noblewoman and comic villainess in Gilbert and Sullivan’s operetta "The Mikado," known for her dramatic presence and unrequited love for Nanki-Poo.
  • D. Kaula
    Kaula is a small, uninhabited rocky islet off the coast of Kauai in Hawaii, known for its steep cliffs, seabird colonies, and use as a U.S. Navy bombing range.
  • E. Kalomo
    Kalomo is a town in southern Zambia that serves as an important local commercial and administrative center for the surrounding agricultural region.
  • 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.