Triple

T3857994
Position Surface form Disambiguated ID Type / Status
Subject Bilen E90064 entity
Predicate hasLinguisticRelation P10003 FINISHED
Object Qimant
Qimant is an endangered Cushitic language of northwestern Ethiopia, traditionally spoken by the Qemant people.
 E392873 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: Qimant | Statement: [Bilen, hasLinguisticRelation, Qimant]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Qimant
Context triple: [Bilen, hasLinguisticRelation, Qimant]
  • A. Helong
    The Helong are an indigenous ethnic group of western Timor known for their distinct Austronesian language and traditional coastal and island communities.
  • B. Tangtse
    Tangtse is a village in the Leh district of Ladakh, India, situated along key routes between the Indus Valley and the Pangong Tso region in the Himalayas.
  • C. Syukuro
    Syukuro is the given name of Syukuro Manabe, a pioneering climatologist known for his foundational work on climate modeling and global warming.
  • D. Yakhin
    Yakhin is a variant form of the biblical name Jachin, traditionally associated with one of the two pillars of Solomon’s Temple.
  • E. Machang
    Machang is a town and administrative district in the Malaysian state of Kelantan, known for its semi-urban character and role as a local commercial and educational hub.
  • 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: Qimant
Triple: [Bilen, hasLinguisticRelation, Qimant]
Generated description
Qimant is an endangered Cushitic language of northwestern Ethiopia, traditionally spoken by the Qemant people.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Qimant
Target entity description: Qimant is an endangered Cushitic language of northwestern Ethiopia, traditionally spoken by the Qemant people.
  • A. Helong
    The Helong are an indigenous ethnic group of western Timor known for their distinct Austronesian language and traditional coastal and island communities.
  • B. Tangtse
    Tangtse is a village in the Leh district of Ladakh, India, situated along key routes between the Indus Valley and the Pangong Tso region in the Himalayas.
  • C. Syukuro
    Syukuro is the given name of Syukuro Manabe, a pioneering climatologist known for his foundational work on climate modeling and global warming.
  • D. Yakhin
    Yakhin is a variant form of the biblical name Jachin, traditionally associated with one of the two pillars of Solomon’s Temple.
  • E. Machang
    Machang is a town and administrative district in the Malaysian state of Kelantan, known for its semi-urban character and role as a local commercial and educational hub.
  • 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_69aed95b3c088190a8f85d19e6070599 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeec1e68f88190941c39221486f6ae completed March 9, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b504228220819082e11b316ba79b08 completed March 14, 2026, 6:45 a.m.
NEDg Description generation batch_69b505420de0819086dee340f34a8886 completed March 14, 2026, 6:50 a.m.
NED2 Entity disambiguation (via description) batch_69b5064192a48190a0f95dee872437e0 completed March 14, 2026, 6:54 a.m.
Created at: March 9, 2026, 3:19 p.m.