Triple
T25542682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sweetener World Tour |
E640212
|
entity |
| Predicate | hasLiveFilm |
P136559
|
FINISHED |
| Object | Ariana Grande: Excuse Me, I Love You |
—
|
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: Ariana Grande: Excuse Me, I Love You | Statement: [Sweetener World Tour, hasLiveFilm, Ariana Grande: Excuse Me, I Love You]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLiveFilm Context triple: [Sweetener World Tour, hasLiveFilm, Ariana Grande: Excuse Me, I Love You]
-
A.
hasLiveActionFilm
Indicates that a subject has a corresponding live-action film adaptation or representation.
-
B.
hasTheatricalFilm
Indicates that an entity has an associated theatrical film adaptation, version, or release.
-
C.
hasInteractiveFilm
Indicates that an entity is associated with, offers, or features an interactive film experience.
-
D.
hasFilmForm
Indicates a relationship where a film is associated with its specific form or format (such as medium, structure, or presentation type).
-
E.
hasLiveVideoRelease
chosen
Indicates that an entity has an associated release of a live video recording.
- F. None of above.
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_69e75dbfff7081909b0aa779d48321d2 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f67257b0448190a13011af81c81449 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 21, 2026, 3:26 p.m.