Triple

T12040030
Position Surface form Disambiguated ID Type / Status
Subject Bemba language E286634 entity
Predicate closelyRelatedTo P37 FINISHED
Object Lala language
The Lala language is a Bantu language of Zambia spoken by the Lala people, closely related to neighboring languages such as Bemba.
 E962195 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: Lala language | Statement: [Bemba language, closelyRelatedTo, Lala language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lala language
Context triple: [Bemba language, closelyRelatedTo, Lala language]
  • A. Lakalai language
    The Lakalai language is an Austronesian language spoken by the Lakalai people of New Britain in Papua New Guinea.
  • B. Laha language
    The Laha language is a lesser-known Kra language spoken by the Laha ethnic group in northern Vietnam.
  • C. Laka language
    Laka language is a lesser-known Adamawa–Ubangi language spoken in parts of Central Africa, particularly in Chad and neighboring regions.
  • D. Palaka language
    The Palaka language is a Senufo language spoken in parts of West Africa, primarily in Ivory Coast, by the Palaka people.
  • E. Larat language
    The Larat language is an Austronesian language spoken on Larat Island in Indonesia’s Tanimbar archipelago.
  • 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: Lala language
Triple: [Bemba language, closelyRelatedTo, Lala language]
Generated description
The Lala language is a Bantu language of Zambia spoken by the Lala people, closely related to neighboring languages such as Bemba.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lala language
Target entity description: The Lala language is a Bantu language of Zambia spoken by the Lala people, closely related to neighboring languages such as Bemba.
  • A. Lakalai language
    The Lakalai language is an Austronesian language spoken by the Lakalai people of New Britain in Papua New Guinea.
  • B. Laha language
    The Laha language is a lesser-known Kra language spoken by the Laha ethnic group in northern Vietnam.
  • C. Laka language
    Laka language is a lesser-known Adamawa–Ubangi language spoken in parts of Central Africa, particularly in Chad and neighboring regions.
  • D. Palaka language
    The Palaka language is a Senufo language spoken in parts of West Africa, primarily in Ivory Coast, by the Palaka people.
  • E. Larat language
    The Larat language is an Austronesian language spoken on Larat Island in Indonesia’s Tanimbar archipelago.
  • 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_69d6ab4669e48190b59246358b0383ab completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9040c1a6c8190aea1388e82dd8f5a completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f49d9937a08190b2f606a1e55733b5 completed May 1, 2026, 12:33 p.m.
NEDg Description generation batch_69f53d9460bc8190869f2b7d095d98cb completed May 1, 2026, 11:56 p.m.
NED2 Entity disambiguation (via description) batch_69f564ed64008190bfbeaf0991a7c2b8 completed May 2, 2026, 2:43 a.m.
Created at: April 8, 2026, 9:47 p.m.