Triple
T9421119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malika |
E227152
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Maleeka |
E227152
|
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: Maleeka | Statement: [Malika, hasVariant, Maleeka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maleeka Context triple: [Malika, hasVariant, Maleeka]
-
A.
Dameisha
Dameisha is a popular coastal area in Shenzhen, China, best known for its long sandy beach, seaside resorts, and recreational attractions.
-
B.
Nakia
Nakia is a 1970s American television drama series centered on a Native American deputy sheriff navigating crime and cultural tensions in a small New Mexico town.
-
C.
Nakia
Nakia is a skilled Wakandan spy and warrior in the Marvel Cinematic Universe, known for her courage, compassion, and close ties to T’Challa and Wakanda.
-
D.
Katisha
Katisha is a formidable, older noblewoman and comic villainess in Gilbert and Sullivan’s operetta "The Mikado," known for her dramatic presence and unrequited love for Nanki-Poo.
-
E.
Malika
chosen
Malika is a feminine given name of Arabic origin commonly used in various Muslim-majority and North African cultures.
- 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_69ca84359e7c819091148ba4b670e436 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd6c2528c8819087b0a21e703254b7 |
completed | April 1, 2026, 7:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d107c95c9481909957b99cacf5e045 |
completed | April 4, 2026, 12:44 p.m. |
Created at: March 30, 2026, 7:48 p.m.