Triple
T13757130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love & Hip Hop |
E330504
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object |
Toby Barraud
Toby Barraud is a television producer best known for his executive production work on the reality TV franchise "Love & Hip Hop."
|
E1059209
|
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: Toby Barraud | Statement: [Love & Hip Hop, executiveProducer, Toby Barraud]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Toby Barraud Context triple: [Love & Hip Hop, executiveProducer, Toby Barraud]
-
A.
Toby Rowland
Toby Rowland is a tech entrepreneur best known as a co-founder of the mobile gaming company behind the hit game Candy Crush Saga.
-
B.
Toby Wright
Toby Wright is an American record producer and engineer best known for his work on influential rock and metal albums, including projects with Alice in Chains.
-
C.
Toby Parkes
Toby Parkes is an actor known for his role in the British dark comedy film "Keeping Mum."
-
D.
Toby Barker
Toby Barker is an American politician who serves as the mayor of Hattiesburg, Mississippi.
-
E.
Toby Carvery
Toby Carvery is a British pub-restaurant chain known for its traditional roast dinners and carvery-style service.
- 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: Toby Barraud Triple: [Love & Hip Hop, executiveProducer, Toby Barraud]
Generated description
Toby Barraud is a television producer best known for his executive production work on the reality TV franchise "Love & Hip Hop."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Toby Barraud Target entity description: Toby Barraud is a television producer best known for his executive production work on the reality TV franchise "Love & Hip Hop."
-
A.
Toby Rowland
Toby Rowland is a tech entrepreneur best known as a co-founder of the mobile gaming company behind the hit game Candy Crush Saga.
-
B.
Toby Wright
Toby Wright is an American record producer and engineer best known for his work on influential rock and metal albums, including projects with Alice in Chains.
-
C.
Toby Parkes
Toby Parkes is an actor known for his role in the British dark comedy film "Keeping Mum."
-
D.
Toby Barker
Toby Barker is an American politician who serves as the mayor of Hattiesburg, Mississippi.
-
E.
Toby Carvery
Toby Carvery is a British pub-restaurant chain known for its traditional roast dinners and carvery-style service.
- 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_69d81c573f288190aa2403d484fa3d49 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de022286b481908f8a801042743512 |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7a85dfa6881908da90886db4aa1bb |
completed | May 3, 2026, 7:56 p.m. |
| NEDg | Description generation | batch_69f7a994cd688190a077a4854c5c71c9 |
completed | May 3, 2026, 8:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7aa32b8c8819088bbc9e478c21c06 |
completed | May 3, 2026, 8:04 p.m. |
Created at: April 9, 2026, 10:09 p.m.