Triple
T21018853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hot 97 |
E517749
|
entity |
| Predicate | notablePersonality |
P7128
|
FINISHED |
| Object |
Laura Stylez
Laura Stylez is a radio host and media personality best known as a co-host of Hot 97’s flagship morning show in New York City.
|
E1462909
|
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: Laura Stylez | Statement: [Hot 97, notablePersonality, Laura Stylez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laura Stylez Context triple: [Hot 97, notablePersonality, Laura Stylez]
-
A.
Stefanie
Stefanie is a feminine given name of German origin, commonly used in German-speaking and other European countries.
-
B.
Laura Laurent
Laura Laurent is a song by the American indie rock band Bright Eyes from their album "Lifted or The Story Is in the Soil, Keep Your Ear to the Ground."
-
C.
Kelly LaRue
Kelly LaRue is a fictional character from the 1990s action-adventure television series "Thunder in Paradise."
-
D.
Amy Stryker
Amy Stryker is an American actress known for her roles in 1970s and 1980s film and television productions.
-
E.
Laura Nigro
Laura Nigro, better known as Laura Nyro, was an influential American singer-songwriter celebrated for her innovative blend of pop, soul, jazz, and folk music in the late 1960s and 1970s.
- 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: Laura Stylez Triple: [Hot 97, notablePersonality, Laura Stylez]
Generated description
Laura Stylez is a radio host and media personality best known as a co-host of Hot 97’s flagship morning show in New York City.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Laura Stylez Target entity description: Laura Stylez is a radio host and media personality best known as a co-host of Hot 97’s flagship morning show in New York City.
-
A.
Stefanie
Stefanie is a feminine given name of German origin, commonly used in German-speaking and other European countries.
-
B.
Laura Laurent
Laura Laurent is a song by the American indie rock band Bright Eyes from their album "Lifted or The Story Is in the Soil, Keep Your Ear to the Ground."
-
C.
Kelly LaRue
Kelly LaRue is a fictional character from the 1990s action-adventure television series "Thunder in Paradise."
-
D.
Amy Stryker
Amy Stryker is an American actress known for her roles in 1970s and 1980s film and television productions.
-
E.
Laura Nigro
Laura Nigro, better known as Laura Nyro, was an influential American singer-songwriter celebrated for her innovative blend of pop, soul, jazz, and folk music in the late 1960s and 1970s.
- 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_69e0b50262b081909bc488937145eb73 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc5b6af4819081fd3aa5212f17a5 |
completed | April 21, 2026, 4:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a093b67103081908033c57e586afa69 |
completed | May 17, 2026, 3:52 a.m. |
| NEDg | Description generation | batch_6a0940b362388190a78a244eafa7cbba |
completed | May 17, 2026, 4:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09414912d88190b7da0186ef7b227f |
completed | May 17, 2026, 4:17 a.m. |
Created at: April 16, 2026, 1:54 p.m.