Triple

T4582052
Position Surface form Disambiguated ID Type / Status
Subject Amhara E101876 entity
Predicate traditionalClothing P271 FINISHED
Object habesha kemis
The habesha kemis is a traditional Ethiopian and Eritrean dress, typically a long white cotton gown adorned with colorful woven borders, commonly worn by women for cultural and religious celebrations.
 E455099 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: habesha kemis | Statement: [Amhara, traditionalClothing, habesha kemis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: habesha kemis
Context triple: [Amhara, traditionalClothing, habesha kemis]
  • A. Hemiksem
    Hemiksem is a municipality in the Belgian province of Antwerp, situated along the Rupel River and known for its historical abbey and industrial heritage.
  • B. Chamical
    Chamical is a small city in central La Rioja Province, Argentina, known historically as a regional railway and agricultural center.
  • C. Kalemie
    Kalemie is a port city in the Democratic Republic of the Congo on the western shore of Lake Tanganyika, serving as a regional transport and trade hub.
  • D. KEM
    KEM is the IATA airport code for Kemi-Tornio Airport in northern Finland.
  • E. Challex
    Challex is a small commune in eastern France’s Ain department, near the Swiss border in the Auvergne-Rhône-Alpes region.
  • 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: habesha kemis
Triple: [Amhara, traditionalClothing, habesha kemis]
Generated description
The habesha kemis is a traditional Ethiopian and Eritrean dress, typically a long white cotton gown adorned with colorful woven borders, commonly worn by women for cultural and religious celebrations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: habesha kemis
Target entity description: The habesha kemis is a traditional Ethiopian and Eritrean dress, typically a long white cotton gown adorned with colorful woven borders, commonly worn by women for cultural and religious celebrations.
  • A. Hemiksem
    Hemiksem is a municipality in the Belgian province of Antwerp, situated along the Rupel River and known for its historical abbey and industrial heritage.
  • B. Chamical
    Chamical is a small city in central La Rioja Province, Argentina, known historically as a regional railway and agricultural center.
  • C. Kalemie
    Kalemie is a port city in the Democratic Republic of the Congo on the western shore of Lake Tanganyika, serving as a regional transport and trade hub.
  • D. KEM
    KEM is the IATA airport code for Kemi-Tornio Airport in northern Finland.
  • E. Challex
    Challex is a small commune in eastern France’s Ain department, near the Swiss border in the Auvergne-Rhône-Alpes region.
  • 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_69bd43d4ce208190b53158c882b222e3 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd590116e88190b8495b2a78cf3fb6 completed March 20, 2026, 2:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69bde098a5a08190873cb0aaa04890a1 completed March 21, 2026, 12:04 a.m.
NEDg Description generation batch_69bde34584348190a6b180774a542234 completed March 21, 2026, 12:16 a.m.
NED2 Entity disambiguation (via description) batch_69bde3c85ac08190b4f8c619e19c2055 completed March 21, 2026, 12:18 a.m.
Created at: March 20, 2026, 1:10 p.m.