Triple
T7660354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kazi Hayat |
E173487
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object |
Kazi Maruf
Kazi Maruf is a Bangladeshi film actor known for his leading roles in commercial Dhallywood cinema.
|
E679452
|
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: Kazi Maruf | Statement: [Kazi Hayat, hasChild, Kazi Maruf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kazi Maruf Context triple: [Kazi Hayat, hasChild, Kazi Maruf]
-
A.
Husuni Ndogo
Husuni Ndogo is a small medieval coastal fortification on Kilwa Kisiwani in Tanzania, associated with the historic Swahili trading civilization.
-
B.
Hany Mukhtar
Hany Mukhtar is a German professional soccer player and attacking midfielder known as a star playmaker and MVP-caliber performer for Nashville SC in Major League Soccer.
-
C.
Johnstone Kamau
Johnstone Kamau is the birth name of Jomo Kenyatta, the prominent Kenyan nationalist leader and first president of independent Kenya.
-
D.
Ngozi Olejeme
Ngozi Olejeme is a Nigerian politician and businesswoman known for her roles in public service and involvement in national development initiatives.
-
E.
Ngethe Njoroge
Ngethe Njoroge is a Kenyan diplomat and journalist known for his work in international relations and as the father of musician Tom Morello.
- 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: Kazi Maruf Triple: [Kazi Hayat, hasChild, Kazi Maruf]
Generated description
Kazi Maruf is a Bangladeshi film actor known for his leading roles in commercial Dhallywood cinema.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kazi Maruf Target entity description: Kazi Maruf is a Bangladeshi film actor known for his leading roles in commercial Dhallywood cinema.
-
A.
Husuni Ndogo
Husuni Ndogo is a small medieval coastal fortification on Kilwa Kisiwani in Tanzania, associated with the historic Swahili trading civilization.
-
B.
Hany Mukhtar
Hany Mukhtar is a German professional soccer player and attacking midfielder known as a star playmaker and MVP-caliber performer for Nashville SC in Major League Soccer.
-
C.
Johnstone Kamau
Johnstone Kamau is the birth name of Jomo Kenyatta, the prominent Kenyan nationalist leader and first president of independent Kenya.
-
D.
Ngozi Olejeme
Ngozi Olejeme is a Nigerian politician and businesswoman known for her roles in public service and involvement in national development initiatives.
-
E.
Ngethe Njoroge
Ngethe Njoroge is a Kenyan diplomat and journalist known for his work in international relations and as the father of musician Tom Morello.
- 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_69c69955517c819085bc715b96d304d2 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c701a47a5c8190867e39f552c86787 |
completed | March 27, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c89b14b6848190892a262903d78b79 |
completed | March 29, 2026, 3:23 a.m. |
| NEDg | Description generation | batch_69c89becbf148190b1f065f4016a6d03 |
completed | March 29, 2026, 3:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c89cc3a3788190bd91aa0995b96c26 |
completed | March 29, 2026, 3:30 a.m. |
Created at: March 27, 2026, 3:59 p.m.