Triple
T13599697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Champagne Showers |
E324911
|
entity |
| Predicate | featuredArtist |
P997
|
FINISHED |
| Object | Natalia Kills |
E324914
|
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: Natalia Kills | Statement: [Champagne Showers, featuredArtist, Natalia Kills]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Natalia Kills Context triple: [Champagne Showers, featuredArtist, Natalia Kills]
-
A.
Natalia Kills
chosen
Natalia Kills is a British singer, songwriter, and producer known for her dark pop sound and provocative visual style.
-
B.
Mel Hinds
Mel Hinds is a child of American R&B and soul singer-songwriter Macy Gray.
-
C.
Vanessa Kensington
Vanessa Kensington is a British intelligence agent and love interest in the Austin Powers film series, portrayed by Elizabeth Hurley.
-
D.
Nataly Dawn
Nataly Dawn is an American singer-songwriter and bassist best known as one half of the indie music duo Pomplamoose.
-
E.
Kate Chastain
Kate Chastain is an American reality television personality and former chief stewardess best known for her prominent role on Bravo’s yachting series "Below Deck."
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb0795acc8190a08667ab9dcb0d44 |
completed | April 12, 2026, 2:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f76bcc1ed88190bbf6c83001703b84 |
completed | May 3, 2026, 3:37 p.m. |
Created at: April 9, 2026, 9:49 p.m.