Triple

T1743095
Position Surface form Disambiguated ID Type / Status
Subject Yunnan Province E38274 entity
Predicate ethnicGroup P194 FINISHED
Object Hani
The Hani are an ethnic minority group in China, primarily known for their terraced rice farming, distinctive traditional dress, and rich folk culture in the mountainous regions of Yunnan.
 E197135 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: Hani | Statement: [Yunnan Province, ethnicGroup, Hani]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hani
Context triple: [Yunnan Province, ethnicGroup, Hani]
  • A. Hana
    Hana is a small, remote town on the eastern coast of Maui, Hawaii, known for its lush landscapes, waterfalls, and the scenic Road to Hana.
  • B. Hana
    Hana is a compassionate Canadian army nurse in Michael Ondaatje's novel "The English Patient," who cares for a badly burned man in an abandoned Italian villa during World War II.
  • C. Hanan
    Hanan is a given name most notably borne by Palestinian legislator, activist, and scholar Hanan Ashrawi.
  • D. Haya
    Haya is a feminine given name of Arabic origin, commonly used in the Middle East and among Arabic-speaking communities.
  • E. Shira
    Shira is the eroded western volcanic cone and plateau of Mount Kilimanjaro, forming one of the mountain’s three main summits.
  • 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: Hani
Triple: [Yunnan Province, ethnicGroup, Hani]
Generated description
The Hani are an ethnic minority group in China, primarily known for their terraced rice farming, distinctive traditional dress, and rich folk culture in the mountainous regions of Yunnan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hani
Target entity description: The Hani are an ethnic minority group in China, primarily known for their terraced rice farming, distinctive traditional dress, and rich folk culture in the mountainous regions of Yunnan.
  • A. Hana
    Hana is a small, remote town on the eastern coast of Maui, Hawaii, known for its lush landscapes, waterfalls, and the scenic Road to Hana.
  • B. Hana
    Hana is a compassionate Canadian army nurse in Michael Ondaatje's novel "The English Patient," who cares for a badly burned man in an abandoned Italian villa during World War II.
  • C. Hanan
    Hanan is a given name most notably borne by Palestinian legislator, activist, and scholar Hanan Ashrawi.
  • D. Haya
    Haya is a feminine given name of Arabic origin, commonly used in the Middle East and among Arabic-speaking communities.
  • E. Shira
    Shira is the eroded western volcanic cone and plateau of Mount Kilimanjaro, forming one of the mountain’s three main summits.
  • 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_69a8862b01a48190ab47209063af82d9 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa63c836d48190bd44ea24977aba2d completed March 6, 2026, 5:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada0dbc7c081909d637c5a482389ef completed March 8, 2026, 4:16 p.m.
NEDg Description generation batch_69ada2c12e208190a9c0051107cd61b0 completed March 8, 2026, 4:24 p.m.
NED2 Entity disambiguation (via description) batch_69ada4dfc9188190845a4e4490318d68 completed March 8, 2026, 4:33 p.m.
Created at: March 4, 2026, 7:31 p.m.