Triple

T7019352
Position Surface form Disambiguated ID Type / Status
Subject Jambojet E162778 entity
Predicate cityServed P82 FINISHED
Object Ukunda
Ukunda is a coastal town in Kenya near Diani Beach, known as a popular tourist destination with a small airstrip serving regional flights.
 E637680 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: Ukunda | Statement: [Jambojet, cityServed, Ukunda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ukunda
Context triple: [Jambojet, cityServed, Ukunda]
  • A. Ngundu
    Ngundu is a small settlement in southern Zimbabwe that serves as a roadside stop and trading center along major routes between Harare and Beitbridge.
  • B. Tunduma
    Tunduma is a border town in southern Tanzania that serves as a major road and rail gateway for trade and travel between Tanzania and Zambia.
  • C. Ushguli
    Ushguli is a remote highland village community in Georgia’s Svaneti region, renowned for its medieval stone towers, well-preserved Svan culture, and status as one of the highest continuously inhabited settlements in Europe.
  • D. Ubungo
    Ubungo is an administrative district and urban area within the city of Dar es Salaam in eastern Tanzania.
  • E. Umtata
    Umtata is the former name of Mthatha, a town in South Africa’s Eastern Cape that serves as a regional economic and administrative center.
  • 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: Ukunda
Triple: [Jambojet, cityServed, Ukunda]
Generated description
Ukunda is a coastal town in Kenya near Diani Beach, known as a popular tourist destination with a small airstrip serving regional flights.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ukunda
Target entity description: Ukunda is a coastal town in Kenya near Diani Beach, known as a popular tourist destination with a small airstrip serving regional flights.
  • A. Ngundu
    Ngundu is a small settlement in southern Zimbabwe that serves as a roadside stop and trading center along major routes between Harare and Beitbridge.
  • B. Tunduma
    Tunduma is a border town in southern Tanzania that serves as a major road and rail gateway for trade and travel between Tanzania and Zambia.
  • C. Ushguli
    Ushguli is a remote highland village community in Georgia’s Svaneti region, renowned for its medieval stone towers, well-preserved Svan culture, and status as one of the highest continuously inhabited settlements in Europe.
  • D. Ubungo
    Ubungo is an administrative district and urban area within the city of Dar es Salaam in eastern Tanzania.
  • E. Umtata
    Umtata is the former name of Mthatha, a town in South Africa’s Eastern Cape that serves as a regional economic and administrative center.
  • 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_69c6885b26248190a857541e3d10e299 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6e1e8e36c81908c95a8181781cda4 completed March 27, 2026, 8 p.m.
NED1 Entity disambiguation (via context triple) batch_69c775707e30819088b311a1a87eee79 completed March 28, 2026, 6:30 a.m.
NEDg Description generation batch_69c77c260d2c8190bb802ca8ce388a00 completed March 28, 2026, 6:58 a.m.
NED2 Entity disambiguation (via description) batch_69c77c944bf081909335db68da464b4f completed March 28, 2026, 7 a.m.
Created at: March 27, 2026, 2:34 p.m.