Triple

T14839600
Position Surface form Disambiguated ID Type / Status
Subject Abemama Atoll E348923 entity
Predicate hasSettlement P1068 FINISHED
Object Kabuna
Kabuna is a small village located on Abemama Atoll in the island nation of Kiribati in the central Pacific Ocean.
 E1121864 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: Kabuna | Statement: [Abemama Atoll, hasSettlement, Kabuna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kabuna
Context triple: [Abemama Atoll, hasSettlement, Kabuna]
  • A. Kabuna
    Kabuna is a small village located on the atoll of Tabiteuea in the island nation of Kiribati in the central Pacific Ocean.
  • B. Dongo
    Dongo is a small town on the northwestern shore of Lake Como in Lombardy, Italy, known for its role in the capture of Benito Mussolini at the end of World War II.
  • C. Komo
    The Komo are an ethnic group indigenous to western Ethiopia, particularly associated with the Gambela Region, with their own distinct language and cultural traditions.
  • D. Komo
    Komo is a town located in Hela Province in the Highlands region of Papua New Guinea.
  • E. Okapa
    Okapa is a rural town in Papua New Guinea known for its highland culture and production of premium coffee.
  • 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: Kabuna
Triple: [Abemama Atoll, hasSettlement, Kabuna]
Generated description
Kabuna is a small village located on Abemama Atoll in the island nation of Kiribati in the central Pacific Ocean.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kabuna
Target entity description: Kabuna is a small village located on Abemama Atoll in the island nation of Kiribati in the central Pacific Ocean.
  • A. Kabuna
    Kabuna is a small village located on the atoll of Tabiteuea in the island nation of Kiribati in the central Pacific Ocean.
  • B. Dongo
    Dongo is a small town on the northwestern shore of Lake Como in Lombardy, Italy, known for its role in the capture of Benito Mussolini at the end of World War II.
  • C. Komo
    Komo is a town located in Hela Province in the Highlands region of Papua New Guinea.
  • D. Komo
    The Komo are an ethnic group indigenous to western Ethiopia, particularly associated with the Gambela Region, with their own distinct language and cultural traditions.
  • E. Okapa
    Okapa is a rural town in Papua New Guinea known for its highland culture and production of premium coffee.
  • 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_69d822ec69008190a9232caa68836872 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded28e40f08190b309d8ac6404d2fc completed April 14, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe38a9eb9481908ca509f484007cf6 completed May 8, 2026, 7:25 p.m.
NEDg Description generation batch_69fe3d0eca948190b107bc593b6e5b72 completed May 8, 2026, 7:44 p.m.
NED2 Entity disambiguation (via description) batch_69fe3d94785881908911a7c6f1546d45 completed May 8, 2026, 7:46 p.m.
Created at: April 10, 2026, 1:52 a.m.