Triple
T3377077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BT TV |
E71089
|
entity |
| Predicate | contentSources |
P17306
|
FINISHED |
| Object | My5 |
E247103
|
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: My5 | Statement: [BT TV, contentSources, My5]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: My5 Context triple: [BT TV, contentSources, My5]
-
A.
Mi TV
Mi TV is a line of smart televisions by Xiaomi that run on the Android TV platform, offering integrated streaming apps and smart features.
-
B.
Channel 5
chosen
Channel 5 is a British free-to-air television network known for a mix of entertainment, documentaries, and imported programming.
-
C.
MVY
MVY is the IATA airport code for Martha's Vineyard Airport, the primary commercial airport serving Martha's Vineyard in Massachusetts, USA.
-
D.
My9
My9 is the on-air brand name used by New York City television station WWOR-TV, a MyNetworkTV-affiliated channel serving the New York metropolitan area.
-
E.
MTV3
MTV3 is one of Finland’s largest commercial television channels, known for its wide range of entertainment, news, and sports programming.
- 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_69ad85a7f80c8190a05e43013f298942 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb2e8d1988190b6fb6c4c5502f25f |
completed | March 8, 2026, 5:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b334490bf08190aa119e72d12f5e4b |
completed | March 12, 2026, 9:46 p.m. |
Created at: March 8, 2026, 3:13 p.m.