Triple
T4231167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dilras Banu Begum |
E94583
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Zeb-un-Nissa |
E97359
|
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: Zeb-un-Nissa | Statement: [Dilras Banu Begum, child, Zeb-un-Nissa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zeb-un-Nissa Context triple: [Dilras Banu Begum, child, Zeb-un-Nissa]
-
A.
Zeb-un-Nissa
chosen
Zeb-un-Nissa was a Mughal princess and noted Persian-language poet renowned for her literary works and intellectual pursuits in 17th-century India.
-
B.
Juwayriya
Juwayriya was a wife of the Prophet Muhammad and is regarded as one of the Mothers of the Believers in Islamic tradition.
-
C.
Rawdah
Rawdah is the revered area between the Prophet Muhammad’s tomb and his pulpit in Al-Masjid an-Nabawi in Medina, considered one of the holiest sites in Islam.
-
D.
Nuzha
Nuzha is a residential district in Kuwait City known for its quiet neighborhoods and local amenities.
-
E.
Rumaitha
Rumaitha is a town in southern Iraq notable as one of the centers of resistance during the 1920 Iraqi revolt against British rule.
- 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_69b34537cc6481909cd0a96acbb33ef7 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e62e3c881909ffb9269ba9018b9 |
completed | March 12, 2026, 11:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5a85fdbe08190bcdc18a4bc456b59 |
completed | March 14, 2026, 6:26 p.m. |
Created at: March 12, 2026, 11:05 p.m.