Triple

T10289186
Position Surface form Disambiguated ID Type / Status
Subject Jacoba E241315 entity
Predicate hasShortForm P43 FINISHED
Object Coba
Coba is a Dutch feminine given name, typically used as a diminutive or short form of Jacoba.
 E852234 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: Coba | Statement: [Jacoba, hasShortForm, Coba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Coba
Context triple: [Jacoba, hasShortForm, Coba]
  • A. Tiba
    Tiba is a modern planned city in Egypt’s Luxor Governorate, developed to accommodate population growth and support regional economic and urban expansion.
  • B. Koubia
    Koubia is a town in the Middle Guinea region of Guinea that serves as an important local administrative and commercial center.
  • C. Goba
    Goba is a small Ethiopian town in the Oromia Region that serves as a primary gateway and service center for visitors to Bale Mountains National Park.
  • D. Taketa
    Taketa is a small historic city in Japan known for its scenic rural landscapes, hot springs, and castle ruins.
  • E. Cebgo
    Cebgo is a Philippine low-cost regional airline operating domestic routes and serving as a feeder carrier for Cebu Pacific.
  • 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: Coba
Triple: [Jacoba, hasShortForm, Coba]
Generated description
Coba is a Dutch feminine given name, typically used as a diminutive or short form of Jacoba.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Coba
Target entity description: Coba is a Dutch feminine given name, typically used as a diminutive or short form of Jacoba.
  • A. Tiba
    Tiba is a modern planned city in Egypt’s Luxor Governorate, developed to accommodate population growth and support regional economic and urban expansion.
  • B. Koubia
    Koubia is a town in the Middle Guinea region of Guinea that serves as an important local administrative and commercial center.
  • C. Goba
    Goba is a small Ethiopian town in the Oromia Region that serves as a primary gateway and service center for visitors to Bale Mountains National Park.
  • D. Taketa
    Taketa is a small historic city in Japan known for its scenic rural landscapes, hot springs, and castle ruins.
  • E. Cebgo
    Cebgo is a Philippine low-cost regional airline operating domestic routes and serving as a feeder carrier for Cebu Pacific.
  • 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_69d381aaafc08190af475ef58dc16aba completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d2b9d76c8190b1ef6ecf4c1a2a09 completed April 7, 2026, 9:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f8556f4081908390bc5c14dcf560 completed April 9, 2026, 12:52 a.m.
NEDg Description generation batch_69d6fcaee26c8190a19f7d07a63531f6 completed April 9, 2026, 1:11 a.m.
NED2 Entity disambiguation (via description) batch_69d6fd879ab88190b0a47295f5d7ad4d completed April 9, 2026, 1:14 a.m.
Created at: April 6, 2026, 11:41 a.m.