Triple
T5830062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princess Aisha bint Hussein |
E129322
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Aisha |
E546296
|
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: Aisha | Statement: [Princess Aisha bint Hussein, givenName, Aisha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aisha Context triple: [Princess Aisha bint Hussein, givenName, Aisha]
-
A.
Aisha
Aisha is a central female character in Naguib Mahfouz’s novel "Palace of Desire," whose relationships and personal struggles reflect the broader social and emotional tensions of early 20th-century Cairo.
-
B.
Aisha
Aisha is a central female protagonist in Naguib Mahfouz’s novel "Palace Walk," representing the complexities of family life and social change in early 20th-century Cairo.
-
C.
Aisha
Aisha is a singer who performed one of the official songs for the 2022 FIFA World Cup.
-
D.
Aisha
Aisha is a skilled and enigmatic operative who joins the elite black-ops team in the action film "The Losers" (2010).
-
E.
Aisha
chosen
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 (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_69c00849d55481908b4f9f5543e0bf6d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0346905848190a8f541401da05604 |
completed | March 22, 2026, 6:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c107ee88fc8190a6f633ff168b51ed |
completed | March 23, 2026, 9:29 a.m. |
Created at: March 22, 2026, 3:54 p.m.