Triple
T9805224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Telewizja Polska |
E237937
|
entity |
| Predicate | hasChannel |
P8080
|
FINISHED |
| Object | TVP Seriale |
E331132
|
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: TVP Seriale | Statement: [Telewizja Polska, hasChannel, TVP Seriale]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TVP Seriale Context triple: [Telewizja Polska, hasChannel, TVP Seriale]
-
A.
TVP
chosen
TVP is Poland’s national public television broadcaster, operating multiple channels and services across the country.
-
B.
Show TV
Show TV is a major Turkish national television channel known for broadcasting popular entertainment programs, series, and news.
-
C.
Dizi
Dizi is an Omotic language spoken primarily by the Dizi people in southwestern Ethiopia.
-
D.
TVF
TVF is the ICAO airline designator used for Transavia France, a French low-cost carrier.
-
E.
TV
TV is Apple’s media playback and streaming application for watching movies, TV shows, and other video content across Apple devices.
- 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_69ca84dd4608819097ff4ed00feca280 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdab7b67748190ba16ce868f29d13e |
completed | April 1, 2026, 11:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1c45878e481908aa2098eceb44256 |
completed | April 5, 2026, 2:09 a.m. |
Created at: March 30, 2026, 8:29 p.m.