Triple
T582500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jahangir |
E15087
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Sahiba Banu Begum
Sahiba Banu Begum was a Mughal princess and consort associated with the imperial family during the reign of Emperor Jahangir.
|
E74208
|
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: Sahiba Banu Begum | Statement: [Jahangir, spouse, Sahiba Banu Begum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sahiba Banu Begum Context triple: [Jahangir, spouse, Sahiba Banu Begum]
-
A.
Maham Begum
Maham Begum was a chief consort of the Mughal emperor Babur and the mother of his successor, Humayun.
-
B.
Aisha Sultan Begum
Aisha Sultan Begum was a Timurid princess best known as one of the early wives of Babur, the founder of the Mughal Empire.
-
C.
Dildar Begum
Dildar Begum was a consort of the Mughal emperor Babur and the mother of his son Hindal Mirza.
-
D.
Gulbadan Begum
Gulbadan Begum was a Mughal princess and memoirist, best known for writing the Humayun-nama, an important historical account of her half-brother Emperor Humayun’s life and reign.
-
E.
Lutfunnisa Begum
Lutfunnisa Begum was a consort of Siraj ud-Daulah, the last independent Nawab of Bengal in the mid-18th century.
- 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: Sahiba Banu Begum Triple: [Jahangir, spouse, Sahiba Banu Begum]
Generated description
Sahiba Banu Begum was a Mughal princess and consort associated with the imperial family during the reign of Emperor Jahangir.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sahiba Banu Begum Target entity description: Sahiba Banu Begum was a Mughal princess and consort associated with the imperial family during the reign of Emperor Jahangir.
-
A.
Maham Begum
Maham Begum was a chief consort of the Mughal emperor Babur and the mother of his successor, Humayun.
-
B.
Aisha Sultan Begum
Aisha Sultan Begum was a Timurid princess best known as one of the early wives of Babur, the founder of the Mughal Empire.
-
C.
Dildar Begum
Dildar Begum was a consort of the Mughal emperor Babur and the mother of his son Hindal Mirza.
-
D.
Gulbadan Begum
Gulbadan Begum was a Mughal princess and memoirist, best known for writing the Humayun-nama, an important historical account of her half-brother Emperor Humayun’s life and reign.
-
E.
Lutfunnisa Begum
Lutfunnisa Begum was a consort of Siraj ud-Daulah, the last independent Nawab of Bengal in the mid-18th century.
- 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_69a4935783b8819082b77726ec10cc42 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49b85becc8190b4d98c00e5fa7c04 |
completed | March 1, 2026, 8:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5155210dc8190bad32b49703641e2 |
completed | March 2, 2026, 4:42 a.m. |
| NEDg | Description generation | batch_69a51788f870819099271dcb41ee4bda |
completed | March 2, 2026, 4:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a51846caa481909a61fa29a44b7470 |
completed | March 2, 2026, 4:55 a.m. |
Created at: March 1, 2026, 7:33 p.m.