Triple
T8890427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fancy |
E211646
|
entity |
| Predicate | featuredArtist |
P997
|
FINISHED |
| Object | Charli XCX |
E339738
|
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: Charli XCX | Statement: [Fancy, featuredArtist, Charli XCX]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charli XCX Context triple: [Fancy, featuredArtist, Charli XCX]
-
A.
Charli XCX
chosen
Charli XCX is a British pop singer, songwriter, and producer known for her experimental, genre-blending approach to mainstream and hyperpop music.
-
B.
Charli
Charli is a common diminutive or nickname for the given name Charlene.
-
C.
Tove Lo
Tove Lo is a Swedish singer-songwriter and pop artist known for her candid, emotionally raw lyrics and hits like "Habits (Stay High)."
-
D.
Doja Cat
Doja Cat is an American rapper, singer, songwriter, and producer known for her genre-blending pop and hip-hop hits, viral online presence, and visually inventive music videos.
-
E.
Ann-Marie
Ann-Marie is the protagonist of the novel "Eat My Heart Out," a young woman navigating chaotic relationships and identity in contemporary London.
- 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_69ca83907954819096d52a245b635841 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc619188508190aacda410f0b4c98d |
completed | April 1, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfba1e46a48190b7a559f9d9bd348d |
completed | April 3, 2026, 1:01 p.m. |
Created at: March 30, 2026, 6:53 p.m.