Triple

T11093705
Position Surface form Disambiguated ID Type / Status
Subject Lendu language E262318 entity
Predicate neighboringLanguages P16383 FINISHED
Object Hema language
The Hema language is a Central Sudanic language spoken primarily by the Hema people in the northeastern Democratic Republic of the Congo.
 E904346 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: Hema language | Statement: [Lendu language, neighboringLanguages, Hema language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hema language
Context triple: [Lendu language, neighboringLanguages, Hema language]
  • A. Semai language
    The Semai language is an Austroasiatic language spoken by the Semai people, an indigenous Orang Asli group in Peninsular Malaysia.
  • B. Damana language
    The Damana language is an indigenous Chibchan tongue spoken by the Wiwa people of the Sierra Nevada de Santa Marta region in northern Colombia.
  • C. Belhare language
    The Belhare language is a Kiranti language of the Sino-Tibetan family spoken by the Belhare community in eastern Nepal.
  • D. Jahai language
    The Jahai language is an indigenous Mon–Khmer language spoken by the Jahai people, a small hunter-gatherer community in the Malay Peninsula.
  • E. Tanema language
    Tanema is a nearly extinct Oceanic language once spoken on Vanikoro Island in the Temotu Province of the Solomon Islands.
  • 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: Hema language
Triple: [Lendu language, neighboringLanguages, Hema language]
Generated description
The Hema language is a Central Sudanic language spoken primarily by the Hema people in the northeastern Democratic Republic of the Congo.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hema language
Target entity description: The Hema language is a Central Sudanic language spoken primarily by the Hema people in the northeastern Democratic Republic of the Congo.
  • A. Semai language
    The Semai language is an Austroasiatic language spoken by the Semai people, an indigenous Orang Asli group in Peninsular Malaysia.
  • B. Damana language
    The Damana language is an indigenous Chibchan tongue spoken by the Wiwa people of the Sierra Nevada de Santa Marta region in northern Colombia.
  • C. Belhare language
    The Belhare language is a Kiranti language of the Sino-Tibetan family spoken by the Belhare community in eastern Nepal.
  • D. Jahai language
    The Jahai language is an indigenous Mon–Khmer language spoken by the Jahai people, a small hunter-gatherer community in the Malay Peninsula.
  • E. Tanema language
    Tanema is a nearly extinct Oceanic language once spoken on Vanikoro Island in the Temotu Province of the Solomon Islands.
  • 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_69d6aa9a40d88190a373e2c7e48285db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d799ed12d88190a4ad8c346d68f11f completed April 9, 2026, 12:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3e7d3043c8190bdbe0ec51992db0c completed April 18, 2026, 8:21 p.m.
NEDg Description generation batch_69e3f2cbb4708190a328cff473104d14 completed April 18, 2026, 9:08 p.m.
NED2 Entity disambiguation (via description) batch_69e3f497a01881909d1dae70a02e5f97 completed April 18, 2026, 9:16 p.m.
Created at: April 8, 2026, 9:27 p.m.