Triple
T10777726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aliko Dangote |
E254239
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Aliko
Aliko is the first name of Aliko Dangote, a Nigerian billionaire industrialist and one of Africa’s most prominent business magnates.
|
E886255
|
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: Aliko | Statement: [Aliko Dangote, givenName, Aliko]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aliko Context triple: [Aliko Dangote, givenName, Aliko]
-
A.
Kelechi
Kelechi is the Nigerian Igbo middle name of American actress Susan Kelechi Watson, reflecting her West African heritage.
-
B.
Ofolanga
Ofolanga is a small island in the Haʻapai group of Tonga, known for its remote, unspoiled beaches and traditional Polynesian character.
-
C.
Ito Aghayere
Ito Aghayere is a Nigerian-Canadian actress known for her work in television, film, and theater, including portraying Guinan in the Star Trek franchise.
-
D.
Aggrey Awori
Aggrey Awori was a Ugandan politician, former minister, and opposition figure known for his presidential bid and earlier career as a diplomat and academic.
-
E.
Fombio
Fombio is a small municipality in the Lombardy region of northern Italy, known for its rural character and location near the Po River.
- 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: Aliko Triple: [Aliko Dangote, givenName, Aliko]
Generated description
Aliko is the first name of Aliko Dangote, a Nigerian billionaire industrialist and one of Africa’s most prominent business magnates.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aliko Target entity description: Aliko is the first name of Aliko Dangote, a Nigerian billionaire industrialist and one of Africa’s most prominent business magnates.
-
A.
Kelechi
Kelechi is the Nigerian Igbo middle name of American actress Susan Kelechi Watson, reflecting her West African heritage.
-
B.
Ofolanga
Ofolanga is a small island in the Haʻapai group of Tonga, known for its remote, unspoiled beaches and traditional Polynesian character.
-
C.
Ito Aghayere
Ito Aghayere is a Nigerian-Canadian actress known for her work in television, film, and theater, including portraying Guinan in the Star Trek franchise.
-
D.
Aggrey Awori
Aggrey Awori was a Ugandan politician, former minister, and opposition figure known for his presidential bid and earlier career as a diplomat and academic.
-
E.
Fombio
Fombio is a small municipality in the Lombardy region of northern Italy, known for its rural character and location near the Po River.
- 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_69d6aa609f008190a294200aefcb7bd5 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d732c18c3c819089d49e3e4585049e |
completed | April 9, 2026, 5:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de55daf52c8190aee3bca39cdc5d55 |
completed | April 14, 2026, 2:57 p.m. |
| NEDg | Description generation | batch_69de5eacae148190b7ca2da87427572e |
completed | April 14, 2026, 3:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69de6397ff688190b6788489895a5360 |
completed | April 14, 2026, 3:56 p.m. |
Created at: April 8, 2026, 9:16 p.m.