Triple
T6503417
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Women |
E148947
|
entity |
| Predicate | hasTransliteration |
P2508
|
FINISHED |
| Object | An-Nisa |
E148945
|
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: An-Nisa | Statement: [The Women, hasTransliteration, An-Nisa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: An-Nisa Context triple: [The Women, hasTransliteration, An-Nisa]
-
A.
An-Nisa
chosen
An-Nisa is the fourth chapter of the Qur’an, notable for its detailed guidance on social justice, family law, and the rights and responsibilities of women and orphans in Islamic society.
-
B.
Umm al-Mu'minin
Umm al-Mu'minin is an honorific Islamic title meaning "Mother of the Believers," traditionally used for the wives of the Prophet Muhammad.
-
C.
Nabawiyya
Nabawiyya is a character in Naguib Mahfouz’s novel "The Thief and the Dogs," known primarily as the unfaithful wife whose betrayal deeply impacts the protagonist, Said Mahran.
-
D.
Hafsa
Hafsa is a feminine given name of Arabic origin, historically borne by notable Ottoman royal figures such as Ayşe Hafsa Sultan.
-
E.
Fakr-un-Nisa
Fakr-un-Nisa was a member of Tipu Sultan’s family whose tomb lies within the historic Gumbaz mausoleum complex at Srirangapatna in Karnataka, India.
- 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_69c687e9ad288190bae5bcac9c8ac855 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c699647ad08190ac0bfd78907d0c3b |
completed | March 27, 2026, 2:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6d50b15f081909bb7024fa57d528b |
completed | March 27, 2026, 7:05 p.m. |
Created at: March 27, 2026, 1:42 p.m.