Triple
T22631830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Albertina Sisulu |
E558572
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Albertina |
—
|
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: Albertina | Statement: [Albertina Sisulu, givenName, Albertina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Albertina Context triple: [Albertina Sisulu, givenName, Albertina]
-
A.
Albertina
Albertina was the historic University of Königsberg, a prominent Prussian center of learning and research founded in the 16th century.
-
B.
Albertina
chosen
Albertina is a renowned art museum and graphic arts collection in Vienna, Austria, famous for its vast holdings of prints and drawings by masters such as Dürer, Michelangelo, and Picasso.
-
C.
Antoinette
Antoinette is the birth name of Princess Muna al-Hussein, the British-born mother of King Abdullah II of Jordan.
-
D.
Antoinette
Antoinette is a feminine given name of French origin, historically associated with nobility and later borne by various notable figures in the arts and public life.
-
E.
Antoinette
Antoinette is an American hip hop artist known for her late-1980s and early-1990s recordings, including work released through Next Plateau Records.
- 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_69e245467d9881908d6985bd0db7a1f1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f17009ecb0819082f94505b0e2c5b8 |
completed | April 29, 2026, 2:42 a.m. |
Created at: April 17, 2026, 3:02 p.m.