Triple
T11863450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Audacy, Inc. |
E282217
|
entity |
| Predicate | tradedAs |
P2822
|
FINISHED |
| Object | AUD |
E282217
|
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: AUD | Statement: [Audacy, Inc., tradedAs, AUD]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AUD Context triple: [Audacy, Inc., tradedAs, AUD]
-
A.
AUD
chosen
AUD is the stock ticker symbol for Audacy, Inc., a major American audio and radio broadcasting company.
-
B.
AU
Aarhus University (AU) is a major public research university in Aarhus, Denmark, known for its broad range of academic programs and strong international profile.
-
C.
AU
AU is the commonly used abbreviation for the African Union, a continental organization that promotes political and economic cooperation among African states.
-
D.
AU
AU is the commonly used abbreviation for Anna University, a prominent public technical university based in Chennai, India.
-
E.
AU
AU is a German vehicle registration code used on license plates to identify cars registered in the Erzgebirgskreis district of Saxony.
- 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a73883508190a78b5f4ba4a220df |
completed | April 10, 2026, 7:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f281844c048190b5476343113f2436 |
completed | April 29, 2026, 10:09 p.m. |
Created at: April 8, 2026, 9:43 p.m.