Triple
T8466012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Viva Rapid Transit |
E200161
|
entity |
| Predicate | hasRoute |
P4374
|
FINISHED |
| Object | Viva Purple |
E196947
|
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: Viva Purple | Statement: [Viva Rapid Transit, hasRoute, Viva Purple]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Viva Purple Context triple: [Viva Rapid Transit, hasRoute, Viva Purple]
-
A.
Viva
chosen
Viva is a bus rapid transit service in York Region, Ontario, Canada, providing frequent, limited-stop public transportation along major corridors.
-
B.
Viva
Viva is a German music television channel that gained popularity in the 1990s and 2000s for its music videos, pop culture programming, and youth-oriented shows.
-
C.
Velvet
Velvet is a Spanish romantic drama television series set in a 1950s fashion house, focusing on the love story between a seamstress and the heir to the business.
-
D.
Red, Hot and Blue
Red, Hot and Blue is a 1936 Broadway musical comedy with music and lyrics by Cole Porter, known for its witty songs and star-studded original cast.
-
E.
Black and Blue
"Black and Blue" is a bestselling novel by Anna Quindlen that explores domestic abuse and a woman's struggle to escape and rebuild her life.
- 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_69ca83198c4c8190a337bf717d1813f5 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe4d17ec8819093becdaec750aff5 |
completed | March 31, 2026, 3:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce4dda5230819087ab2509eb958fc2 |
completed | April 2, 2026, 11:07 a.m. |
Created at: March 30, 2026, 6:11 p.m.