Triple
T8499022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | kora |
E201168
|
entity |
| Predicate | playedBy |
P9616
|
FINISHED |
| Object |
Jali Nyama Suso
Jali Nyama Suso was a renowned Gambian kora virtuoso and griot celebrated for his mastery of traditional Mandinka music and storytelling.
|
E740017
|
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: Jali Nyama Suso | Statement: [kora, playedBy, Jali Nyama Suso]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jali Nyama Suso Context triple: [kora, playedBy, Jali Nyama Suso]
-
A.
Semeka
Semeka is a former American college basketball player and coach best known for her standout career with the Tennessee Lady Volunteers under Pat Summitt.
-
B.
Machar
Machar is a small rural township in Ontario, Canada, known for its forests, lakes, and low-density residential and agricultural character.
-
C.
Bachué
Bachué is a principal mother goddess in Muisca mythology, associated with creation, fertility, and the origin of humanity.
-
D.
Gambiri Kati
Gambiri Kati is an alternative name for the Tregami language, an Indo-Iranian language spoken in parts of eastern Afghanistan.
-
E.
Dongo
Dongo is a small town on the northwestern shore of Lake Como in Lombardy, Italy, known for its role in the capture of Benito Mussolini at the end of World War II.
- 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: Jali Nyama Suso Triple: [kora, playedBy, Jali Nyama Suso]
Generated description
Jali Nyama Suso was a renowned Gambian kora virtuoso and griot celebrated for his mastery of traditional Mandinka music and storytelling.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jali Nyama Suso Target entity description: Jali Nyama Suso was a renowned Gambian kora virtuoso and griot celebrated for his mastery of traditional Mandinka music and storytelling.
-
A.
Semeka
Semeka is a former American college basketball player and coach best known for her standout career with the Tennessee Lady Volunteers under Pat Summitt.
-
B.
Machar
Machar is a small rural township in Ontario, Canada, known for its forests, lakes, and low-density residential and agricultural character.
-
C.
Bachué
Bachué is a principal mother goddess in Muisca mythology, associated with creation, fertility, and the origin of humanity.
-
D.
Gambiri Kati
Gambiri Kati is an alternative name for the Tregami language, an Indo-Iranian language spoken in parts of eastern Afghanistan.
-
E.
Dongo
Dongo is a small town on the northwestern shore of Lake Como in Lombardy, Italy, known for its role in the capture of Benito Mussolini at the end of World War II.
- 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_69ca831ee390819095fae73400bbfafc |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe5984d7481908c41c57bef9cf254 |
completed | March 31, 2026, 3:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce4e0aa7788190abd7bb259966bc44 |
completed | April 2, 2026, 11:07 a.m. |
| NEDg | Description generation | batch_69ce4ff668d4819081f4c3186437291b |
completed | April 2, 2026, 11:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce54cc52cc81908ca48c93956ca86e |
completed | April 2, 2026, 11:36 a.m. |
Created at: March 30, 2026, 6:14 p.m.