Triple
T20602479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hafsa |
E506217
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object | Hafsa |
—
|
NE NERFINISHED |
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: Hafsa | Statement: [Hafsa, hasComponent, Hafsa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hafsa Context triple: [Hafsa, hasComponent, Hafsa]
-
A.
Hafsa
chosen
Hafsa is a feminine given name of Arabic origin, historically borne by notable Ottoman royal figures such as Ayşe Hafsa Sultan.
-
B.
Habiba
Habiba is a feminine given name commonly used in Arabic-speaking and Muslim-majority cultures, meaning "beloved" or "darling."
-
C.
Khadija
Khadija is a central female character in Naguib Mahfouz’s novel "Palace of Desire," known for her strong will, evolving maturity, and role within the complex dynamics of the Abd al-Jawad family.
-
D.
Zubayda
Zubayda was a prominent Abbasid princess and influential patron of public works, especially known for funding major infrastructure projects like the water system serving pilgrims on the route to Mecca.
-
E.
Aisha
Aisha is a female given name of Arabic origin commonly used across the Muslim world and beyond.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4ba6ae88190af871e1f9522c704 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aa20f5c881909265ce7d96efc487 |
completed | April 20, 2026, 10:35 p.m. |
Created at: April 16, 2026, 11:41 a.m.