Triple
T2243921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ctrl |
E49457
|
entity |
| Predicate | performer |
P1363
|
FINISHED |
| Object | SZA |
E49457
|
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: SZA | Statement: [Ctrl, performer, SZA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SZA Context triple: [Ctrl, performer, SZA]
-
A.
SZA
chosen
SZA is an American R&B singer-songwriter known for her introspective lyrics, genre-blending sound, and critically acclaimed albums like "Ctrl."
-
B.
Maggie Rogers
Maggie Rogers is a fictional African American maid and central character in the television miniseries "Backstairs at the White House," which dramatizes the lives of White House domestic staff across several U.S. presidencies.
-
C.
Kehlani
Kehlani is an American R&B singer, songwriter, and performer known for her emotive vocals, candid lyricism, and genre-blending projects like the mixtape "You Should Be Here" and the album "SweetSexySavage."
-
D.
Jhené Aiko
Jhené Aiko is an American singer and songwriter known for her ethereal vocals and introspective, R&B-influenced music.
-
E.
H.E.R.
H.E.R. is an American R&B singer-songwriter and multi-instrumentalist known for her soulful vocals, introspective lyrics, and Grammy-winning work.
- 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_69a88aa979788190ad6500f1d8eee2fc |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0c157e88190a5bc876d9591a24b |
completed | March 7, 2026, 6:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae71bfb47881908c93333a9e808420 |
completed | March 9, 2026, 7:07 a.m. |
Created at: March 4, 2026, 7:47 p.m.