Triple

T10247921
Position Surface form Disambiguated ID Type / Status
Subject Teke languages E240265 entity
Predicate hasMember P10 FINISHED
Object Teke-Laali language
The Teke-Laali language is a Bantu language spoken by the Teke people of Central Africa, primarily in the Republic of the Congo.
E853704 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: Teke-Laali language | Statement: [Teke languages, hasMember, Teke-Laali language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Teke-Laali language
Context triple: [Teke languages, hasMember, Teke-Laali language]
  • A. Lakalai language
    The Lakalai language is an Austronesian language spoken by the Lakalai people of New Britain in Papua New Guinea.
  • B. Kaera language
    The Kaera language is a Papuan language spoken by a small community on Pantar Island in eastern Indonesia.
  • C. Jakaltek language
    The Jakaltek language is a Mayan language spoken primarily by the Jakaltek (Popti’) people of northwestern Guatemala and parts of southern Mexico.
  • D. Patelia language
    The Patelia language is a regional Indo-Aryan tribal language variety associated with the Bhil communities of western India.
  • E. Teke-Eboo languages
    The Teke-Eboo languages are a subgroup of Bantu languages spoken primarily by Teke-related communities in Central Africa, especially in the Republic of the Congo and surrounding regions.
  • 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: Teke-Laali language
Triple: [Teke languages, hasMember, Teke-Laali language]
Generated description
The Teke-Laali language is a Bantu language spoken by the Teke people of Central Africa, primarily in the Republic of the Congo.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Teke-Laali language
Target entity description: The Teke-Laali language is a Bantu language spoken by the Teke people of Central Africa, primarily in the Republic of the Congo.
  • A. Lakalai language
    The Lakalai language is an Austronesian language spoken by the Lakalai people of New Britain in Papua New Guinea.
  • B. Kaera language
    The Kaera language is a Papuan language spoken by a small community on Pantar Island in eastern Indonesia.
  • C. Jakaltek language
    The Jakaltek language is a Mayan language spoken primarily by the Jakaltek (Popti’) people of northwestern Guatemala and parts of southern Mexico.
  • D. Patelia language
    The Patelia language is a regional Indo-Aryan tribal language variety associated with the Bhil communities of western India.
  • E. Teke-Eboo languages chosen
    The Teke-Eboo languages are a subgroup of Bantu languages spoken primarily by Teke-related communities in Central Africa, especially in the Republic of the Congo and surrounding regions.
  • F. None of above.

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_69d381a7e198819090280d5ab885d59e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d22e0d4c8190a6712859924e9d3d completed April 7, 2026, 9:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69d87e33a0088190b1cad6ada8beb345 completed April 10, 2026, 4:36 a.m.
NEDg Description generation batch_69d886c325c4819089dac35eb26e7961 completed April 10, 2026, 5:12 a.m.
NED2 Entity disambiguation (via description) batch_69d88dbbe97c8190861e08f3ff39f91b completed April 10, 2026, 5:42 a.m.
Created at: April 6, 2026, 11:27 a.m.