Triple

T11166845
Position Surface form Disambiguated ID Type / Status
Subject Lumbu E264180 entity
Predicate ethnicLanguage P11430 FINISHED
Object Lumbu language
Lumbu language is a Bantu language spoken by the Lumbu people, primarily in parts of Gabon and the Republic of the Congo.
 E908714 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: Lumbu language | Statement: [Lumbu, ethnicLanguage, Lumbu language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lumbu language
Context triple: [Lumbu, ethnicLanguage, Lumbu language]
  • A. Medumba language
    Medumba is a Bantu-related Grassfields language spoken primarily by the Bamileke people in western Cameroon.
  • B. Limbu language
    Limbu language is a Sino-Tibetan language spoken primarily by the Limbu ethnic group in eastern Nepal and neighboring regions of India.
  • C. Kumbewaha language
    The Kumbewaha language is an Austronesian language spoken in Sulawesi, Indonesia, belonging to the Wotu–Wolio subgroup.
  • D. Lendu language
    The Lendu language is a Central Sudanic language spoken primarily by the Lendu people in northeastern Democratic Republic of the Congo.
  • E. Lamboya language
    The Lamboya language is an Austronesian language spoken by the Lamboya people on the island of Sumba in eastern Indonesia.
  • 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: Lumbu language
Triple: [Lumbu, ethnicLanguage, Lumbu language]
Generated description
Lumbu language is a Bantu language spoken by the Lumbu people, primarily in parts of Gabon and the Republic of the Congo.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lumbu language
Target entity description: Lumbu language is a Bantu language spoken by the Lumbu people, primarily in parts of Gabon and the Republic of the Congo.
  • A. Medumba language
    Medumba is a Bantu-related Grassfields language spoken primarily by the Bamileke people in western Cameroon.
  • B. Limbu language
    Limbu language is a Sino-Tibetan language spoken primarily by the Limbu ethnic group in eastern Nepal and neighboring regions of India.
  • C. Kumbewaha language
    The Kumbewaha language is an Austronesian language spoken in Sulawesi, Indonesia, belonging to the Wotu–Wolio subgroup.
  • D. Lendu language
    The Lendu language is a Central Sudanic language spoken primarily by the Lendu people in northeastern Democratic Republic of the Congo.
  • E. Lamboya language
    The Lamboya language is an Austronesian language spoken by the Lamboya people on the island of Sumba in eastern Indonesia.
  • 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_69d6aa9dafac8190bd90d2c74f661aa7 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e88843cc81909e503f0921c6d297 completed April 9, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69e463945e40819087c6bdbc322a6d54 completed April 19, 2026, 5:09 a.m.
NEDg Description generation batch_69e46c37efec81908aa709587c37569d completed April 19, 2026, 5:46 a.m.
NED2 Entity disambiguation (via description) batch_69e47292cdd08190b05c4c8b09f4f918 completed April 19, 2026, 6:13 a.m.
Created at: April 8, 2026, 9:29 p.m.