Triple
T10096426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Socialcam |
E215877
|
entity |
| Predicate | competedWith |
P1375
|
FINISHED |
| Object | Viddy |
E841356
|
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: Viddy | Statement: [Socialcam, competedWith, Viddy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Viddy Context triple: [Socialcam, competedWith, Viddy]
-
A.
Viddy
chosen
Viddy was a mobile social video-sharing app that allowed users to create, edit, and share short video clips with an online community.
-
B.
VIDO
VIDO is a Canadian research organization at the University of Saskatchewan specializing in vaccine development and infectious disease research for both humans and animals.
-
C.
Vdio
Vdio was an online video-on-demand and streaming service launched by Skype and Rdio co-founder Janus Friis as an attempt to compete with platforms like Netflix.
-
D.
VIDN
VIDN is the four-letter ICAO airport code assigned to Noida International Airport in Uttar Pradesh, India.
-
E.
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.
- 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_69ca83a4947c8190823a7495dc5d96ed |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd0798c248190af675e30e280daa8 |
completed | April 2, 2026, 2:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2cbeef9a08190a2267f6c7de81170 |
completed | April 5, 2026, 8:54 p.m. |
Created at: March 30, 2026, 9:02 p.m.