Triple
T14660128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shawn Mendes |
E344214
|
entity |
| Predicate | discoveredOn |
P3836
|
FINISHED |
| Object | Vine |
E17427
|
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: Vine | Statement: [Shawn Mendes, discoveredOn, Vine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vine Context triple: [Shawn Mendes, discoveredOn, Vine]
-
A.
Vine
chosen
Vine was a short-form video hosting service and social media platform known for its looping six-second clips and significant cultural impact in the early 2010s.
-
B.
The Vine
The Vine is a public transit service brand used by C-TRAN for its bus and related transportation services in the Vancouver, Washington area.
-
C.
Grapevine
Grapevine is a small unincorporated community located in Berkeley County, West Virginia.
-
D.
Grapevine
Grapevine is a suburban city in the Dallas–Fort Worth metropolitan area known for its historic downtown, wineries, and proximity to Dallas/Fort Worth International Airport.
-
E.
Viddy
Viddy was a mobile social video-sharing app that allowed users to create, edit, and share short video clips with an online community.
- 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_69d822e283fc8190a0e4c235cf880052 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb51c84448190a1f5fa9ab8a1e2c4 |
completed | April 14, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdd5e28f848190a3d686bc11336601 |
completed | May 8, 2026, 12:24 p.m. |
Created at: April 10, 2026, 1:27 a.m.