Triple

T7005378
Position Surface form Disambiguated ID Type / Status
Subject Sophie Okonedo E162440 entity
Predicate familyName P18 FINISHED
Object Okonedo
Okonedo is the surname of Sophie Okonedo, a British actress known for her acclaimed performances in film, television, and theatre.
 E634798 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: Okonedo | Statement: [Sophie Okonedo, familyName, Okonedo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Okonedo
Context triple: [Sophie Okonedo, familyName, Okonedo]
  • A. Oku
    Oku is a town and traditional kingdom in Cameroon's Northwest Region, known for its rich cultural heritage, mountainous landscape, and production of Oku white honey.
  • B. Ōtoku
    Ōtoku was a Japanese era name (nengō) of the late 11th century, used during the reign of Emperor Shirakawa.
  • C. Nengone
    Nengone is an Austronesian language spoken primarily by the indigenous Kanak people on Maré Island in New Caledonia.
  • D. Inoniya
    Inoniya is a work by the renowned Russian poet Sergei Yesenin, reflecting his lyrical and often melancholic style rooted in rural life and emotional introspection.
  • E. Toconao
    Toconao is a small desert village in northern Chile known for its traditional Atacameño culture, adobe architecture, and proximity to the Atacama Desert’s salt flats and high-altitude landscapes.
  • 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: Okonedo
Triple: [Sophie Okonedo, familyName, Okonedo]
Generated description
Okonedo is the surname of Sophie Okonedo, a British actress known for her acclaimed performances in film, television, and theatre.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Okonedo
Target entity description: Okonedo is the surname of Sophie Okonedo, a British actress known for her acclaimed performances in film, television, and theatre.
  • A. Oku
    Oku is a town and traditional kingdom in Cameroon's Northwest Region, known for its rich cultural heritage, mountainous landscape, and production of Oku white honey.
  • B. Ōtoku
    Ōtoku was a Japanese era name (nengō) of the late 11th century, used during the reign of Emperor Shirakawa.
  • C. Nengone
    Nengone is an Austronesian language spoken primarily by the indigenous Kanak people on Maré Island in New Caledonia.
  • D. Inoniya
    Inoniya is a work by the renowned Russian poet Sergei Yesenin, reflecting his lyrical and often melancholic style rooted in rural life and emotional introspection.
  • E. Toconao
    Toconao is a small desert village in northern Chile known for its traditional Atacameño culture, adobe architecture, and proximity to the Atacama Desert’s salt flats and high-altitude landscapes.
  • 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_69c6885928148190ae31909fbb5e9849 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dc34b5a88190a793e07dd4d0018b completed March 27, 2026, 7:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c76a3b2e9c8190b90c4eaaaea983ee completed March 28, 2026, 5:42 a.m.
NEDg Description generation batch_69c76b1ef6f481908f4c4f610328f633 completed March 28, 2026, 5:46 a.m.
NED2 Entity disambiguation (via description) batch_69c76c01679c8190b61f642c23c25ed5 completed March 28, 2026, 5:49 a.m.
Created at: March 27, 2026, 2:33 p.m.