Triple
T5652538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vy |
E124537
|
entity |
| Predicate | ticketingSystem |
P3383
|
FINISHED |
| Object | Vy app |
E508944
|
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: Vy app | Statement: [Vy, ticketingSystem, Vy app]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vy app Context triple: [Vy, ticketingSystem, Vy app]
-
A.
Vy mobile app
chosen
Vy mobile app is a mobile application that allows users to plan journeys and purchase tickets for Vy’s regional train services in Norway.
-
B.
Appar
Appar was a prominent 7th-century Tamil Shaivite saint and poet whose devotional hymns greatly shaped the Bhakti movement in South India.
-
C.
Sky Player
Sky Player was the earlier online television streaming service from Sky in the UK, later rebranded as Sky Go.
-
D.
Syl Apps
Syl Apps was a Canadian professional ice hockey centre and Hall of Famer best known as a star player for the Toronto Maple Leafs in the 1930s and 1940s.
-
E.
Burbn
Burbn was a location-based photo-sharing startup that served as the precursor to and foundation for what became Instagram.
- 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_69c00825df388190a58742fa9b1aa33d |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c022d8a2588190b10de59edbc8841f |
completed | March 22, 2026, 5:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04d97b8dc8190865ff55071954b30 |
completed | March 22, 2026, 8:14 p.m. |
Created at: March 22, 2026, 3:42 p.m.