Triple
T5531241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clarel |
E145051
|
entity |
| Predicate | character |
P662
|
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: [Clarel, character, Vine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vine Context triple: [Clarel, character, 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.
Vignely
Vignely is a small French commune located in the Seine-et-Marne department in the Île-de-France region in north-central France.
-
D.
Viner
Viner is a surname most notably associated with Jacob Viner, a prominent 20th-century economist known for his influential work in international trade theory and economic history.
-
E.
Vuse
Vuse is an electronic cigarette and vaping product brand owned by British American Tobacco, known for its range of nicotine e-liquids and devices.
- 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_69c008f9955881909bfa8348b56b4739 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f9b59bc8190a8758b3be54831e9 |
completed | March 22, 2026, 4:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c02805a174819096cd16f2c1ef2eb1 |
completed | March 22, 2026, 5:33 p.m. |
Created at: March 22, 2026, 3:34 p.m.