Triple
T14698821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jamie Bartlett |
E345234
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Isidingo
Isidingo is a South African television soap opera known for its socially conscious storylines and long-running popularity.
|
E1113742
|
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: Isidingo | Statement: [Jamie Bartlett, notableWork, Isidingo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Isidingo Context triple: [Jamie Bartlett, notableWork, Isidingo]
-
A.
Ingogo
Ingogo is a small rural settlement in the Newcastle Local Municipality of KwaZulu-Natal, South Africa, known historically for its role in the Anglo-Boer conflicts.
-
B.
Mabalako
Mabalako is a health zone in North Kivu Province in the eastern Democratic Republic of the Congo, known for being heavily affected by Ebola outbreaks.
-
C.
Zindziswa
Zindziswa is the given first name of Zindzi Mandela, the South African diplomat, poet, and daughter of Nelson Mandela and Winnie Madikizela-Mandela.
-
D.
Thokoza
Thokoza is a township in the East Rand region of Gauteng, South Africa, historically known for its role in anti-apartheid struggles and community activism.
-
E.
Lungi Ngidi
Lungi Ngidi is a South African fast bowler known for his pace, bounce, and impactful performances in international cricket across formats.
- 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: Isidingo Triple: [Jamie Bartlett, notableWork, Isidingo]
Generated description
Isidingo is a South African television soap opera known for its socially conscious storylines and long-running popularity.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Isidingo Target entity description: Isidingo is a South African television soap opera known for its socially conscious storylines and long-running popularity.
-
A.
Ingogo
Ingogo is a small rural settlement in the Newcastle Local Municipality of KwaZulu-Natal, South Africa, known historically for its role in the Anglo-Boer conflicts.
-
B.
Mabalako
Mabalako is a health zone in North Kivu Province in the eastern Democratic Republic of the Congo, known for being heavily affected by Ebola outbreaks.
-
C.
Zindziswa
Zindziswa is the given first name of Zindzi Mandela, the South African diplomat, poet, and daughter of Nelson Mandela and Winnie Madikizela-Mandela.
-
D.
Thokoza
Thokoza is a township in the East Rand region of Gauteng, South Africa, historically known for its role in anti-apartheid struggles and community activism.
-
E.
Lungi Ngidi
Lungi Ngidi is a South African fast bowler known for his pace, bounce, and impactful performances in international cricket across formats.
- 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_69d822e4a8c08190a155df736bb7bc13 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb604f88081908a677175045496d0 |
completed | April 14, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fde19040e0819099159ed2609c6965 |
completed | May 8, 2026, 1:13 p.m. |
| NEDg | Description generation | batch_69fde43698e881908226ae4907910249 |
completed | May 8, 2026, 1:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fde53290a48190b3701472bb4e3d63 |
completed | May 8, 2026, 1:29 p.m. |
Created at: April 10, 2026, 1:28 a.m.