Triple

T9014902
Position Surface form Disambiguated ID Type / Status
Subject Susu E215569 entity
Predicate primaryLanguage P238 FINISHED
Object Susu language
Susu language is a Mande language of West Africa, primarily spoken by the Susu people in Guinea and neighboring countries.
 E772784 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: Susu language | Statement: [Susu, primaryLanguage, Susu language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Susu language
Context triple: [Susu, primaryLanguage, Susu language]
  • A. Suku language
    Suku language is a Bantu language spoken primarily by the Suku people in the Democratic Republic of the Congo.
  • B. Suma language
    The Suma language is a lesser-known Gbaya language spoken by the Suma people in parts of Central Africa.
  • C. Suwawa language
    The Suwawa language is an Austronesian language spoken by the Suwawa people of northern Sulawesi, Indonesia, and is part of the Gorontalo–Mongondow subgroup.
  • D. Sialum language
    The Sialum language is a Papuan language spoken by the Sialum people of Morobe Province in Papua New Guinea.
  • E. Sawu language
    The Sawu language is an Austronesian language spoken primarily on Savu (Sawu) Island 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: Susu language
Triple: [Susu, primaryLanguage, Susu language]
Generated description
Susu language is a Mande language of West Africa, primarily spoken by the Susu people in Guinea and neighboring countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Susu language
Target entity description: Susu language is a Mande language of West Africa, primarily spoken by the Susu people in Guinea and neighboring countries.
  • A. Suku language
    Suku language is a Bantu language spoken primarily by the Suku people in the Democratic Republic of the Congo.
  • B. Suma language
    The Suma language is a lesser-known Gbaya language spoken by the Suma people in parts of Central Africa.
  • C. Suwawa language
    The Suwawa language is an Austronesian language spoken by the Suwawa people of northern Sulawesi, Indonesia, and is part of the Gorontalo–Mongondow subgroup.
  • D. Sialum language
    The Sialum language is a Papuan language spoken by the Sialum people of Morobe Province in Papua New Guinea.
  • E. Sawu language
    The Sawu language is an Austronesian language spoken primarily on Savu (Sawu) Island 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_69ca83a2bf088190986ee7a8eb90407d completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc69fae0b88190a0aa989bc37ab2c7 completed April 1, 2026, 12:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfdba4bfd481908a5f33d39b8e7dd5 completed April 3, 2026, 3:24 p.m.
NEDg Description generation batch_69cfdc5b230881908057cc868e44ea44 completed April 3, 2026, 3:27 p.m.
NED2 Entity disambiguation (via description) batch_69cfdcfc28288190b849b3f0216a7e9a completed April 3, 2026, 3:30 p.m.
Created at: March 30, 2026, 7:06 p.m.