Triple
T2555431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bing |
E56719
|
entity |
| Predicate | hasSubService |
P40817
|
FINISHED |
| Object | Bing Videos |
E56719
|
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: Bing Videos | Statement: [Bing, hasSubService, Bing Videos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bing Videos Context triple: [Bing, hasSubService, Bing Videos]
-
A.
YouTube
YouTube is a global online video-sharing and streaming platform where users can upload, watch, and interact with a vast range of video content.
-
B.
Bing
chosen
Bing is Microsoft's web search engine that provides internet search, image, video, and mapping services.
-
C.
SVT Play
SVT Play is Sweden’s national public service broadcaster’s online streaming platform, offering on-demand and live TV content.
-
D.
YouTube Shorts
YouTube Shorts is YouTube’s short-form vertical video platform designed for quick, snackable content similar to TikTok and Instagram Reels.
-
E.
AVS
AVS is a professional society focused on advancing the science and technology of materials, interfaces, and processing through research, education, and collaboration.
- 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_69ab4a4bfec081908039988ec4c86e28 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd8317b0481908d6d1436732253b2 |
completed | March 7, 2026, 7:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af5d1ad6b4819097f1d18a12aa2b89 |
completed | March 9, 2026, 11:51 p.m. |
Created at: March 6, 2026, 9:48 p.m.