Triple
T2602241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Audacy, Inc. |
E58370
|
entity |
| Predicate | hasBrand |
P1500
|
FINISHED |
| Object |
BetQL Network
BetQL Network is a sports betting-focused media network providing analysis, odds, and wagering insights across radio and digital platforms.
|
E282214
|
NE FINISHED |
How this triple was built (4 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: BetQL Network | Statement: [Audacy, Inc., hasBrand, BetQL Network]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BetQL Network Context triple: [Audacy, Inc., hasBrand, BetQL Network]
-
A.
Meta River
The Meta River is a major waterway in Colombia and Venezuela that drains the eastern Andes and Llanos plains before joining the Orinoco River.
-
B.
DB Netz
DB Netz is the infrastructure division of Deutsche Bahn responsible for operating and maintaining Germany’s national railway network.
-
C.
Jepsen
Jepsen is a surname most notably associated with individuals such as display technology innovator Mary Lou Jepsen.
-
D.
Bee Network
Bee Network is Greater Manchester’s integrated public transport system brand, unifying buses, trams, cycling and walking under a single, coordinated network.
-
E.
Canvas Network
Canvas Network is an online learning platform that hosts and delivers massive open online courses (MOOCs) from universities and institutions worldwide.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: BetQL Network Triple: [Audacy, Inc., hasBrand, BetQL Network]
Generated description
BetQL Network is a sports betting-focused media network providing analysis, odds, and wagering insights across radio and digital platforms.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: BetQL Network Target entity description: BetQL Network is a sports betting-focused media network providing analysis, odds, and wagering insights across radio and digital platforms.
-
A.
Meta River
The Meta River is a major waterway in Colombia and Venezuela that drains the eastern Andes and Llanos plains before joining the Orinoco River.
-
B.
DB Netz
DB Netz is the infrastructure division of Deutsche Bahn responsible for operating and maintaining Germany’s national railway network.
-
C.
Jepsen
Jepsen is a surname most notably associated with individuals such as display technology innovator Mary Lou Jepsen.
-
D.
Bee Network
Bee Network is Greater Manchester’s integrated public transport system brand, unifying buses, trams, cycling and walking under a single, coordinated network.
-
E.
Canvas Network
Canvas Network is an online learning platform that hosts and delivers massive open online courses (MOOCs) from universities and institutions worldwide.
- F. None of above. chosen
Provenance (5 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_69ab4ac14040819098b13f4a27d5c8ff |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd459ca6c81908505be96d097b739 |
completed | March 7, 2026, 7:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af83d37de081909467f8caa17ce3a9 |
completed | March 10, 2026, 2:37 a.m. |
| NEDg | Description generation | batch_69af8501adc4819092035d7e55524fc8 |
completed | March 10, 2026, 2:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69af85a6060c8190a80d5633d1b8a9d5 |
completed | March 10, 2026, 2:44 a.m. |
Created at: March 6, 2026, 9:49 p.m.