Triple
T6596220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hasan Banu Begum |
E148481
|
entity |
| Predicate | nobleRank |
P914
|
FINISHED |
| Object | begum |
E106849
|
NE FINISHED |
How this triple was built (2 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: begum | Statement: [Hasan Banu Begum, nobleRank, begum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: begum Context triple: [Hasan Banu Begum, nobleRank, begum]
-
A.
Begum
chosen
Begum is an honorific title historically used in South Asia for Muslim women of high social rank, especially queens, princesses, and noblewomen.
-
B.
Umid Bega Begum
Umid Bega Begum was a Timurid noblewoman known primarily as a wife of Umar Sheikh Mirza II and thus a member of the Mughal imperial family’s ancestral lineage.
-
C.
Hazrat Begum
Hazrat Begum was a Mughal princess who became one of the wives of Ahmad Shah Durrani, the founder of the Durrani Empire in Afghanistan.
-
D.
Haji Begum
Haji Begum was a Mughal empress and chief consort of Emperor Humayun, best known for overseeing the construction of his grand mausoleum in Delhi.
-
E.
Hasan Banu Begum
Hasan Banu Begum was a Mughal noblewoman known primarily as one of the wives of the emperor Shah Jahan.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c687e7b8688190811ffee72e096468 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6aeecdd4c819092b87f4c91883154 |
completed | March 27, 2026, 4:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6e42fc9ec8190a6bb19010337d516 |
completed | March 27, 2026, 8:10 p.m. |
Created at: March 27, 2026, 1:56 p.m.