Triple

T6505122
Position Surface form Disambiguated ID Type / Status
Subject Southeast Sulawesi E149987 entity
Predicate hasIsland P970 FINISHED
Object Kabaena
Kabaena is an island in Indonesia known for its location off the coast of Sulawesi and its mix of coastal and hilly landscapes.
 E600664 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: Kabaena | Statement: [Southeast Sulawesi, hasIsland, Kabaena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kabaena
Context triple: [Southeast Sulawesi, hasIsland, Kabaena]
  • A. Kandia
    Kandia is a remote valley and settlement area located within Pakistan’s Kohistan mountain ranges, known for its rugged terrain and isolated communities.
  • B. Mazabuka
    Mazabuka is a town in southern Zambia known for its sugar industry and agricultural production.
  • C. Chambeali
    Chambeali is an Indo-Aryan language spoken primarily in the Chamba region of Himachal Pradesh in northern India.
  • D. Buhera
    Buhera is a rural town and district center in eastern Zimbabwe known for its agricultural activities and location within Manicaland Province.
  • E. Nabaloi
    Nabaloi is an Austronesian language spoken by the Ibaloi people of the northern Philippines, particularly in the Benguet region of Luzon.
  • 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: Kabaena
Triple: [Southeast Sulawesi, hasIsland, Kabaena]
Generated description
Kabaena is an island in Indonesia known for its location off the coast of Sulawesi and its mix of coastal and hilly landscapes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kabaena
Target entity description: Kabaena is an island in Indonesia known for its location off the coast of Sulawesi and its mix of coastal and hilly landscapes.
  • A. Kandia
    Kandia is a remote valley and settlement area located within Pakistan’s Kohistan mountain ranges, known for its rugged terrain and isolated communities.
  • B. Mazabuka
    Mazabuka is a town in southern Zambia known for its sugar industry and agricultural production.
  • C. Chambeali
    Chambeali is an Indo-Aryan language spoken primarily in the Chamba region of Himachal Pradesh in northern India.
  • D. Buhera
    Buhera is a rural town and district center in eastern Zimbabwe known for its agricultural activities and location within Manicaland Province.
  • E. Nabaloi
    Nabaloi is an Austronesian language spoken by the Ibaloi people of the northern Philippines, particularly in the Benguet region of Luzon.
  • 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_69c687ef291081909d437f035eef1cda completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c69966ff708190902c88cb6b48e5d7 completed March 27, 2026, 2:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cb43db608190b785e77f6850bb6f completed March 27, 2026, 6:24 p.m.
NEDg Description generation batch_69c6cc96edd08190b0c0f1b49dd64160 completed March 27, 2026, 6:29 p.m.
NED2 Entity disambiguation (via description) batch_69c6cd8d15ec8190be5a8c5e3f201139 completed March 27, 2026, 6:33 p.m.
Created at: March 27, 2026, 1:43 p.m.