Triple
T19999237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Street Outlaws |
E494273
|
entity |
| Predicate | featuresCastMember |
P7010
|
FINISHED |
| Object |
AZN
AZN is a street racer and television personality best known for his appearances on the reality TV series "Street Outlaws."
|
E1405422
|
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: AZN | Statement: [Street Outlaws, featuresCastMember, AZN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AZN Context triple: [Street Outlaws, featuresCastMember, AZN]
-
A.
AZN
AZN is the IATA airport code for Andijan Airport, a regional air transport hub serving the city of Andijan in eastern Uzbekistan.
-
B.
AZN
AZN is the stock ticker symbol for AstraZeneca, a major global biopharmaceutical company known for developing prescription medicines across several therapeutic areas.
-
C.
AZU
AZU is the ICAO airline designator for Azul Brazilian Airlines, a major low-cost carrier based in Brazil.
-
D.
AZD
AZD is a common shorthand used to refer to the Arizona Diamondbacks, a Major League Baseball team based in Phoenix, Arizona.
-
E.
Azna
Azna is a small city in western Iran known for its location in the mountainous Lorestan region and its role as a local administrative and commercial center.
- 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: AZN Triple: [Street Outlaws, featuresCastMember, AZN]
Generated description
AZN is a street racer and television personality best known for his appearances on the reality TV series "Street Outlaws."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: AZN Target entity description: AZN is a street racer and television personality best known for his appearances on the reality TV series "Street Outlaws."
-
A.
AZN
AZN is the IATA airport code for Andijan Airport, a regional air transport hub serving the city of Andijan in eastern Uzbekistan.
-
B.
AZN
AZN is the stock ticker symbol for AstraZeneca, a major global biopharmaceutical company known for developing prescription medicines across several therapeutic areas.
-
C.
AZU
AZU is the ICAO airline designator for Azul Brazilian Airlines, a major low-cost carrier based in Brazil.
-
D.
AZD
AZD is a common shorthand used to refer to the Arizona Diamondbacks, a Major League Baseball team based in Phoenix, Arizona.
-
E.
Azna
Azna is a small city in western Iran known for its location in the mountainous Lorestan region and its role as a local administrative and commercial center.
- 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_69da626b2d748190886981ea90c8b2ea |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e661a09bdc819083305b08a11c6e34 |
completed | April 20, 2026, 5:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a080509d0748190a2703a2e3ddb0fc1 |
completed | May 16, 2026, 5:47 a.m. |
| NEDg | Description generation | batch_6a0806563e1c8190b702fcfc009c84d5 |
completed | May 16, 2026, 5:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0806e876c881909f0c30e5dd16ce20 |
completed | May 16, 2026, 5:55 a.m. |
Created at: April 11, 2026, 3:32 p.m.