Triple

T13219049
Position Surface form Disambiguated ID Type / Status
Subject Sena–Nyanja languages E314699 entity
Predicate hasMemberLanguage P7390 FINISHED
Object Mang’anja
Mang’anja is a Bantu language variety spoken primarily in southern Malawi, closely related to other Sena–Nyanja languages.
E1028424 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: Mang’anja | Statement: [Sena–Nyanja languages, hasMemberLanguage, Mang’anja]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mang’anja
Context triple: [Sena–Nyanja languages, hasMemberLanguage, Mang’anja]
  • A. Munji
    Munji is a lesser-known Eastern Iranian language spoken by the Munji people in the remote Munjan Valley of northeastern Afghanistan.
  • B. Mangshi
    Mangshi is a county-level city in southwestern Yunnan, China, known as the political and economic center of the Dehong Dai and Jingpo Autonomous Prefecture.
  • C. Machang
    Machang is a town and administrative district in the Malaysian state of Kelantan, known for its semi-urban character and role as a local commercial and educational hub.
  • D. Mahwa
    Mahwa is a town located in the Dausa district of the Indian state of Rajasthan.
  • E. Maonan
    The Maonan are a small ethnic minority group in southern China known for their distinct Kam–Sui language, traditional rice farming, and rich folk customs.
  • 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: Mang’anja
Triple: [Sena–Nyanja languages, hasMemberLanguage, Mang’anja]
Generated description
Mang’anja is a Bantu language variety spoken primarily in southern Malawi, closely related to other Sena–Nyanja languages.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mang’anja
Target entity description: Mang’anja is a Bantu language variety spoken primarily in southern Malawi, closely related to other Sena–Nyanja languages.
  • A. Munji
    Munji is a lesser-known Eastern Iranian language spoken by the Munji people in the remote Munjan Valley of northeastern Afghanistan.
  • B. Mangshi
    Mangshi is a county-level city in southwestern Yunnan, China, known as the political and economic center of the Dehong Dai and Jingpo Autonomous Prefecture.
  • C. Machang
    Machang is a town and administrative district in the Malaysian state of Kelantan, known for its semi-urban character and role as a local commercial and educational hub.
  • D. Mahwa
    Mahwa is a town located in the Dausa district of the Indian state of Rajasthan.
  • E. Maonan
    The Maonan are a small ethnic minority group in southern China known for their distinct Kam–Sui language, traditional rice farming, and rich folk customs.
  • 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_69d806affc688190a25b6ccc588e9c72 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98cf392e08190949ee4d194566395 completed April 10, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6ff2085f88190be8cfc309d21f9cb completed May 3, 2026, 7:54 a.m.
NEDg Description generation batch_69f7036009808190aea595cd542e0cf1 completed May 3, 2026, 8:12 a.m.
NED2 Entity disambiguation (via description) batch_69f7040e32a4819083a9f4efe96fd9ca completed May 3, 2026, 8:15 a.m.
Created at: April 9, 2026, 9:18 p.m.