Triple

T7946035
Position Surface form Disambiguated ID Type / Status
Subject Miao languages E184499 entity
Predicate hasMemberLanguage P7390 FINISHED
Object Hmu
Hmu is a major Hmong-Mien (Miao) language spoken primarily by the Miao people in southern China, noted for its complex tonal system and rich oral tradition.
 E704483 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: Hmu | Statement: [Miao languages, hasMemberLanguage, Hmu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hmu
Context triple: [Miao languages, hasMemberLanguage, Hmu]
  • A. MUHA
    MUHA is the ICAO airport code for José Martí International Airport, the main international gateway serving Havana, Cuba.
  • B. Muhu
    Muhu is a large Estonian island in the Baltic Sea known for its traditional villages, distinctive folk culture, and role as a gateway between the mainland and Saaremaa.
  • C. Muh-he-con-neok
    Muh-he-con-neok is an alternative historical name for the Mahican, a Native American people originally from the Hudson River Valley region.
  • D. Hau
    Hau is the surname of Danish physicist Lene Vestergaard Hau, known for her pioneering work in slowing and stopping light.
  • E. Bimoba
    Bimoba are an ethnic group primarily inhabiting parts of northern Ghana and neighboring areas of Togo, known for their distinct language and cultural traditions.
  • 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: Hmu
Triple: [Miao languages, hasMemberLanguage, Hmu]
Generated description
Hmu is a major Hmong-Mien (Miao) language spoken primarily by the Miao people in southern China, noted for its complex tonal system and rich oral tradition.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hmu
Target entity description: Hmu is a major Hmong-Mien (Miao) language spoken primarily by the Miao people in southern China, noted for its complex tonal system and rich oral tradition.
  • A. MUHA
    MUHA is the ICAO airport code for José Martí International Airport, the main international gateway serving Havana, Cuba.
  • B. Muhu
    Muhu is a large Estonian island in the Baltic Sea known for its traditional villages, distinctive folk culture, and role as a gateway between the mainland and Saaremaa.
  • C. Muh-he-con-neok
    Muh-he-con-neok is an alternative historical name for the Mahican, a Native American people originally from the Hudson River Valley region.
  • D. Hau
    Hau is the surname of Danish physicist Lene Vestergaard Hau, known for her pioneering work in slowing and stopping light.
  • E. Bimoba
    Bimoba are an ethnic group primarily inhabiting parts of northern Ghana and neighboring areas of Togo, known for their distinct language and cultural traditions.
  • 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_69ca8291c2008190b1b8832c87814bcf completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3b29a570819091a2ac185a8d57c4 completed March 31, 2026, 3:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe02faa308190aeba83cc6cb96153 completed March 31, 2026, 2:54 p.m.
NEDg Description generation batch_69cbe4383d0c819085e7c95e7b0be16e completed March 31, 2026, 3:11 p.m.
NED2 Entity disambiguation (via description) batch_69cc34a83cec81908aba7afbaea53449 completed March 31, 2026, 8:55 p.m.
Created at: March 30, 2026, 5:09 p.m.