Triple
T7963745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fally Ipupa |
E184943
|
entity |
| Predicate | associatedAct |
P37
|
FINISHED |
| Object |
MHD
MHD is a French rapper known for pioneering the Afro trap genre, blending hip-hop with African musical influences.
|
E703358
|
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: MHD | Statement: [Fally Ipupa, associatedAct, MHD]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MHD Context triple: [Fally Ipupa, associatedAct, MHD]
-
A.
MDC
MDC is a Zimbabwean opposition political party known as the Movement for Democratic Change, which has played a major role in challenging the long-standing rule of ZANU–PF.
-
B.
IHE MHD
IHE MHD (Mobile Access to Health Documents) is an IHE profile that defines a standardized, RESTful, FHIR-based way to access, query, and exchange clinical documents and metadata in healthcare systems.
-
C.
MDH
MDH is the commonly used abbreviation for the Faculty of Medicine, Dentistry and Health, an academic division focused on education and research in medical, dental and health sciences.
-
D.
MDH
MDH is the acronym for the Maryland Department of Health, the state agency responsible for public health services, policy, and regulation in Maryland.
-
E.
MAD
MAD is a museum dedicated to contemporary art and design, showcasing innovative and experimental works across various media.
- 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: MHD Triple: [Fally Ipupa, associatedAct, MHD]
Generated description
MHD is a French rapper known for pioneering the Afro trap genre, blending hip-hop with African musical influences.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MHD Target entity description: MHD is a French rapper known for pioneering the Afro trap genre, blending hip-hop with African musical influences.
-
A.
MDC
MDC is a Zimbabwean opposition political party known as the Movement for Democratic Change, which has played a major role in challenging the long-standing rule of ZANU–PF.
-
B.
IHE MHD
IHE MHD (Mobile Access to Health Documents) is an IHE profile that defines a standardized, RESTful, FHIR-based way to access, query, and exchange clinical documents and metadata in healthcare systems.
-
C.
MDH
MDH is the commonly used abbreviation for the Faculty of Medicine, Dentistry and Health, an academic division focused on education and research in medical, dental and health sciences.
-
D.
MDH
MDH is the acronym for the Maryland Department of Health, the state agency responsible for public health services, policy, and regulation in Maryland.
-
E.
MAD
MAD is a museum dedicated to contemporary art and design, showcasing innovative and experimental works across various media.
- 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_69ca8293a2388190aace944d7ed9c0c0 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b9f577481908589d10fdc486abb |
completed | March 31, 2026, 3:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe093f00881909317eb4dd4fa1393 |
completed | March 31, 2026, 2:56 p.m. |
| NEDg | Description generation | batch_69cbe43b20148190ba9a4dd00a9f5862 |
completed | March 31, 2026, 3:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc3307ebd481908c1ec4b0be270a77 |
completed | March 31, 2026, 8:48 p.m. |
Created at: March 30, 2026, 5:12 p.m.