Triple
T7992072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al-Wahid |
E186031
|
entity |
| Predicate | isPartOf |
P10
|
FINISHED |
| Object | Asma ul-Husna |
E155399
|
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: Asma ul-Husna | Statement: [Al-Wahid, isPartOf, Asma ul-Husna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Asma ul-Husna Context triple: [Al-Wahid, isPartOf, Asma ul-Husna]
-
A.
Asma ul Husna
chosen
Asma ul Husna refers to the 99 beautiful names of Allah in Islamic tradition, each expressing a distinct divine attribute.
-
B.
Hafsa
Hafsa is a feminine given name of Arabic origin, historically borne by notable Ottoman royal figures such as Ayşe Hafsa Sultan.
-
C.
Sayyida Nafisa
Sayyida Nafisa was a revered 9th-century Muslim saint and descendant of the Prophet Muhammad, known for her piety, scholarship, and spiritual influence in Cairo.
-
D.
Asma bint Umais
Asma bint Umais was a notable early Muslim woman and Companion of the Prophet Muhammad, known for her piety, multiple marriages to prominent companions, and participation in the early migrations of Islam.
-
E.
Muhsinah
Muhsinah is an American singer, songwriter, and producer known for her eclectic, futuristic soul sound and collaborations in alternative hip-hop and R&B.
- 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_69ca829c6c308190ab05b43d234c52b2 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c712d0481908d163d2509d054fa |
completed | March 31, 2026, 3:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe0fe312c81908c6874fa0aabe7d5 |
completed | March 31, 2026, 2:58 p.m. |
Created at: March 30, 2026, 5:16 p.m.