Triple
T4289788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zeb-un-Nissa |
E97359
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object | Zubdat-un-Nissa |
E421679
|
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: Zubdat-un-Nissa | Statement: [Zeb-un-Nissa, sibling, Zubdat-un-Nissa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zubdat-un-Nissa Context triple: [Zeb-un-Nissa, sibling, Zubdat-un-Nissa]
-
A.
Zubdat-un-Nissa
chosen
Zubdat-un-Nissa was a Mughal princess, the daughter of Emperor Aurangzeb and his chief consort Dilras Banu Begum.
-
B.
Risaletü’n-Nushiyye
Risaletü’n-Nushiyye is a didactic Sufi mesnevi by Yunus Emre that offers moral and spiritual guidance in poetic form.
-
C.
Al-Kisāʾī
Al-Kisāʾī was a prominent early Arabic grammarian and Qurʾān reciter, renowned as one of the leading scholars of the Kufan linguistic tradition.
-
D.
Kitab al-Sab'in
Kitab al-Sab'in is a seminal alchemical treatise attributed to the early Islamic polymath Jabir ibn Hayyan, exploring theoretical and practical aspects of chemistry and transmutation.
-
E.
Rübab-ı Şikeste
Rübab-ı Şikeste is a seminal poetry collection by Ottoman poet Tevfik Fikret that helped shape modern Turkish literature with its innovative style and themes.
- 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_69b3454595848190a0e6bbb6a2bea040 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35061f5448190b3356b29a9129160 |
completed | March 12, 2026, 11:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5c7307e3481909dfb55018f359589 |
completed | March 14, 2026, 8:38 p.m. |
Created at: March 12, 2026, 11:08 p.m.