Triple
T107114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alicia Keys |
E2161
|
entity |
| Predicate | album |
P1995
|
FINISHED |
| Object | Alicia |
E25209
|
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: Alicia | Statement: [Alicia Keys, album, Alicia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alicia Context triple: [Alicia Keys, album, Alicia]
-
A.
Alicia
chosen
Alicia is the given name of the American singer, songwriter, and pianist Alicia Keys, known for her soulful R&B music and powerful vocals.
-
B.
Alicia Nash
Alicia Nash was a Salvadoran-American physicist and mental health advocate best known as the devoted wife of mathematician John Nash, whose life with him was portrayed in the film "A Beautiful Mind."
-
C.
Barbara
Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
-
D.
Angela
Angela is the given name of Angela Merkel, the long-serving former Chancellor of Germany and a prominent European political leader.
-
E.
Nancy
Nancy is a feminine given name of Hebrew origin meaning "grace" that became especially popular in English-speaking countries in the 20th century.
- 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_69a24e0a5b7c81908d52da08c60dabc4 |
completed | Feb. 28, 2026, 2:08 a.m. |
| NER | Named-entity recognition | batch_69a25b7e2c188190b1dd8aafd4507a99 |
completed | Feb. 28, 2026, 3:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3232a3f8c81909aaf3479415828f4 |
completed | Feb. 28, 2026, 5:17 p.m. |
Created at: Feb. 28, 2026, 2:12 a.m.