Triple

T6219434
Position Surface form Disambiguated ID Type / Status
Subject Makua languages E139072 entity
Predicate hasMember P10 FINISHED
Object Koti language
Koti language is a Bantu language spoken primarily along the coast of Mozambique, closely related to other Makua languages.
 E578696 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: Koti language | Statement: [Makua languages, hasMember, Koti language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Koti language
Context triple: [Makua languages, hasMember, Koti language]
  • A. Kati language
    The Kati language is a Nuristani language spoken primarily in parts of northeastern Afghanistan and adjacent regions of Pakistan.
  • B. Kokota language
    The Kokota language is an Austronesian language spoken by the Kokota people of Santa Isabel Island in the Solomon Islands.
  • C. Koiits language
    The Koiits language is a lesser-known Kiranti language spoken by an indigenous community in the eastern Himalayan region of Nepal.
  • D. Kioko language
    The Kioko language is an Austronesian language of the Muna–Buton subgroup spoken by a small community in southeastern Sulawesi, Indonesia.
  • E. Koya language
    Koya language is a South-Central Dravidian language spoken by the Koya tribal communities in central and southern India.
  • 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: Koti language
Triple: [Makua languages, hasMember, Koti language]
Generated description
Koti language is a Bantu language spoken primarily along the coast of Mozambique, closely related to other Makua languages.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Koti language
Target entity description: Koti language is a Bantu language spoken primarily along the coast of Mozambique, closely related to other Makua languages.
  • A. Kati language
    The Kati language is a Nuristani language spoken primarily in parts of northeastern Afghanistan and adjacent regions of Pakistan.
  • B. Kokota language
    The Kokota language is an Austronesian language spoken by the Kokota people of Santa Isabel Island in the Solomon Islands.
  • C. Koiits language
    The Koiits language is a lesser-known Kiranti language spoken by an indigenous community in the eastern Himalayan region of Nepal.
  • D. Kioko language
    The Kioko language is an Austronesian language of the Muna–Buton subgroup spoken by a small community in southeastern Sulawesi, Indonesia.
  • E. Koya language
    Koya language is a South-Central Dravidian language spoken by the Koya tribal communities in central and southern India.
  • 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_69c008aecb0c81909984b48f733ce8ae completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062bbb768819099402d367f124639 completed March 22, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c20dbbacf08190bbbb2863e19c3e7c completed March 24, 2026, 4:06 a.m.
NEDg Description generation batch_69c214980bbc8190b188b3c821ea13ea completed March 24, 2026, 4:35 a.m.
NED2 Entity disambiguation (via description) batch_69c2157d43048190a0376cdc9024c5f9 completed March 24, 2026, 4:39 a.m.
Created at: March 22, 2026, 4:21 p.m.