Triple

T10922595
Position Surface form Disambiguated ID Type / Status
Subject Mijikenda E257983 entity
Predicate hasPart P35 FINISHED
Object Ribe
Ribe is one of the traditional settlements or sub-groups associated with the Mijikenda people of the Kenyan coast, known for its cultural and historical significance.
 E893983 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: Ribe | Statement: [Mijikenda, hasPart, Ribe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ribe
Context triple: [Mijikenda, hasPart, Ribe]
  • A. Ribe
    Ribe is the oldest town in Denmark, known for its well-preserved medieval center and Viking heritage.
  • B. Havelberg
    Havelberg is a small historic town in Saxony-Anhalt, Germany, known for its medieval cathedral and location at the confluence of the Havel and Elbe rivers.
  • C. Viborg
    Viborg is one of Denmark’s oldest cities, historically significant as a medieval political and religious center on the Jutland peninsula.
  • D. Viborg
    Viborg is the Swedish name for the historic Karelian city of Vyborg, located near the Finnish border on the Gulf of Finland.
  • E. Hellebæk
    Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
  • 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: Ribe
Triple: [Mijikenda, hasPart, Ribe]
Generated description
Ribe is one of the traditional settlements or sub-groups associated with the Mijikenda people of the Kenyan coast, known for its cultural and historical significance.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ribe
Target entity description: Ribe is one of the traditional settlements or sub-groups associated with the Mijikenda people of the Kenyan coast, known for its cultural and historical significance.
  • A. Ribe
    Ribe is the oldest town in Denmark, known for its well-preserved medieval center and Viking heritage.
  • B. Havelberg
    Havelberg is a small historic town in Saxony-Anhalt, Germany, known for its medieval cathedral and location at the confluence of the Havel and Elbe rivers.
  • C. Viborg
    Viborg is the Swedish name for the historic Karelian city of Vyborg, located near the Finnish border on the Gulf of Finland.
  • D. Viborg
    Viborg is one of Denmark’s oldest cities, historically significant as a medieval political and religious center on the Jutland peninsula.
  • E. Hellebæk
    Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
  • 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_69d6aa864ed88190818280ab6791d065 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7708d1fb88190bb33b72d4330ce11 completed April 9, 2026, 9:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2172894d88190b7b27f78e9fd1521 completed April 17, 2026, 11:19 a.m.
NEDg Description generation batch_69e21d8a2e6881909b33cbe4ab919315 completed April 17, 2026, 11:46 a.m.
NED2 Entity disambiguation (via description) batch_69e21eaa1e9881909f3b276e0ff0c511 completed April 17, 2026, 11:51 a.m.
Created at: April 8, 2026, 9:22 p.m.