Triple

T11792165
Position Surface form Disambiguated ID Type / Status
Subject East Central Sudanic languages E280413 entity
Predicate hasMember P10 FINISHED
Object Lulubo language
The Lulubo language is a Nilo-Saharan language spoken by the Lulubo people of South Sudan.
 E947163 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: Lulubo language | Statement: [East Central Sudanic languages, hasMember, Lulubo language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lulubo language
Context triple: [East Central Sudanic languages, hasMember, Lulubo language]
  • A. Baliledu language
    The Baliledu language is an Austronesian language of the Bima–Sumba subgroup spoken by a local community in eastern Indonesia.
  • B. Lumbu language
    Lumbu language is a Bantu language spoken by the Lumbu people, primarily in parts of Gabon and the Republic of the Congo.
  • C. Asilulu language
    The Asilulu language is an Austronesian language spoken by the Asilulu people on Ambon Island in Indonesia’s Maluku province.
  • D. Tembe language
    The Tembe language is an indigenous Tupi-Guarani language spoken by the Tembé people of northern Brazil.
  • E. Lugbara language
    The Lugbara language is a Central Sudanic language spoken primarily by the Lugbara people of northwestern Uganda and northeastern Democratic Republic of the Congo.
  • 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: Lulubo language
Triple: [East Central Sudanic languages, hasMember, Lulubo language]
Generated description
The Lulubo language is a Nilo-Saharan language spoken by the Lulubo people of South Sudan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lulubo language
Target entity description: The Lulubo language is a Nilo-Saharan language spoken by the Lulubo people of South Sudan.
  • A. Baliledu language
    The Baliledu language is an Austronesian language of the Bima–Sumba subgroup spoken by a local community in eastern Indonesia.
  • B. Lumbu language
    Lumbu language is a Bantu language spoken by the Lumbu people, primarily in parts of Gabon and the Republic of the Congo.
  • C. Asilulu language
    The Asilulu language is an Austronesian language spoken by the Asilulu people on Ambon Island in Indonesia’s Maluku province.
  • D. Tembe language
    The Tembe language is an indigenous Tupi-Guarani language spoken by the Tembé people of northern Brazil.
  • E. Lugbara language
    The Lugbara language is a Central Sudanic language spoken primarily by the Lugbara people of northwestern Uganda and northeastern Democratic Republic of the Congo.
  • 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_69d6ab258b808190b1735835c841e3a4 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a588d2c881909783c2d678c2a474 completed April 10, 2026, 7:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69f130fd7b9881909e79ecb49fe98d30 completed April 28, 2026, 10:13 p.m.
NEDg Description generation batch_69f141b1c50c819081a8055d951a49de completed April 28, 2026, 11:24 p.m.
NED2 Entity disambiguation (via description) batch_69f14fcb63208190ad1185ad66314fa9 completed April 29, 2026, 12:24 a.m.
Created at: April 8, 2026, 9:42 p.m.