Triple
T7772415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Razzak |
E179102
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Laily Begum
Laily Begum is known as the wife of Bangladeshi film actor Razzak, a prominent figure in the country’s cinema history.
|
E687723
|
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: Laily Begum | Statement: [Razzak, spouse, Laily Begum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laily Begum Context triple: [Razzak, spouse, Laily Begum]
-
A.
Wafa Begum
Wafa Begum was a queen consort of the Durrani Empire as the wife of Afghan ruler Shuja Shah Durrani.
-
B.
Jani Begum
Jani Begum was a Mughal royal consort known primarily as the wife of Emperor Azam Shah, son of Aurangzeb.
-
C.
Munny Begum
Munny Begum was a prominent consort of Nawab Mir Jafar of Bengal who wielded considerable influence in the late 18th-century Nawabi court.
-
D.
Shahnaz Lalarukh
Shahnaz Lalarukh is the elder sister of Bollywood actor Shah Rukh Khan, known for maintaining a very private life away from the film industry.
-
E.
Sarai Alamgir
Sarai Alamgir is a town in Punjab, Pakistan, situated along the Jhelum River and known for its strategic location on the historic Grand Trunk Road.
- 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: Laily Begum Triple: [Razzak, spouse, Laily Begum]
Generated description
Laily Begum is known as the wife of Bangladeshi film actor Razzak, a prominent figure in the country’s cinema history.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Laily Begum Target entity description: Laily Begum is known as the wife of Bangladeshi film actor Razzak, a prominent figure in the country’s cinema history.
-
A.
Wafa Begum
Wafa Begum was a queen consort of the Durrani Empire as the wife of Afghan ruler Shuja Shah Durrani.
-
B.
Jani Begum
Jani Begum was a Mughal royal consort known primarily as the wife of Emperor Azam Shah, son of Aurangzeb.
-
C.
Munny Begum
Munny Begum was a prominent consort of Nawab Mir Jafar of Bengal who wielded considerable influence in the late 18th-century Nawabi court.
-
D.
Shahnaz Lalarukh
Shahnaz Lalarukh is the elder sister of Bollywood actor Shah Rukh Khan, known for maintaining a very private life away from the film industry.
-
E.
Sarai Alamgir
Sarai Alamgir is a town in Punjab, Pakistan, situated along the Jhelum River and known for its strategic location on the historic Grand Trunk Road.
- 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_69c69f30602c819082ab52cd4af5c592 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c7046048688190a6cbc64e82b58eca |
completed | March 27, 2026, 10:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8c7ee407881908e591d216c504b24 |
completed | March 29, 2026, 6:34 a.m. |
| NEDg | Description generation | batch_69c8c8b84f88819086ecd371b62e2b5b |
completed | March 29, 2026, 6:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8c917a1308190ab2c8e70d6ed8c0e |
completed | March 29, 2026, 6:39 a.m. |
Created at: March 27, 2026, 4:11 p.m.