Triple
T19574384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Football League |
E489812
|
entity |
| Predicate | televisionPartner |
P833
|
FINISHED |
| Object | HDNet |
—
|
NE NERFINISHED |
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: HDNet | Statement: [United Football League, televisionPartner, HDNet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HDNet Context triple: [United Football League, televisionPartner, HDNet]
-
A.
HDNet
chosen
HDNet is an American high-definition television network co-founded by Mark Cuban, known for airing news, sports, and entertainment programming.
-
B.
HDX
HDX is an open humanitarian data platform that enables organizations to share, find, and use data for crisis preparedness and response.
-
C.
HD1
HD1 was a French television channel that later became known as TF1 Séries Films, focusing on series and film programming.
-
D.
HDTV
HDTV (High-Definition Television) is a television broadcasting standard that delivers significantly higher resolution, improved picture clarity, and better color quality compared to traditional standard-definition TV.
-
E.
HDAM
HDAM is the ICAO airport code for Djibouti–Ambouli International Airport, the main international airport serving Djibouti.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8dd9374819098e36349b3211663 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6402333dc8190bdffb1da68e2c76b |
completed | April 20, 2026, 3:02 p.m. |
Created at: April 10, 2026, 1:42 p.m.