Triple
T3952298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Timothy Mosley |
E84891
|
entity |
| Predicate | notableAlias |
P39
|
FINISHED |
| Object |
DJ Timmy Tim
DJ Timmy Tim is an early stage name of Timothy Mosley, the influential American record producer and rapper better known as Timbaland.
|
E402543
|
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: DJ Timmy Tim | Statement: [Timothy Mosley, notableAlias, DJ Timmy Tim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DJ Timmy Tim Context triple: [Timothy Mosley, notableAlias, DJ Timmy Tim]
-
A.
DJ Toomp
DJ Toomp is an American record producer and DJ best known for his influential work in Southern hip hop, including crafting hits for artists like T.I. and Kanye West.
-
B.
Dum Dum Dugan
Dum Dum Dugan is a gruff, mustachioed World War II-era soldier and close ally of Nick Fury in Marvel Comics, renowned for his combat skills and leadership within elite military units.
-
C.
Count von Count
Count von Count is a friendly, number-obsessed vampire Muppet who teaches children basic counting skills on the television show Sesame Street.
-
D.
Dandy Dan
Dandy Dan is the sharply dressed, ruthless mob boss antagonist in the 1976 musical gangster film "Bugsy Malone."
-
E.
Elvin
Elvin is a masculine given name most notably associated with Hall of Fame basketball player Elvin Hayes.
- 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: DJ Timmy Tim Triple: [Timothy Mosley, notableAlias, DJ Timmy Tim]
Generated description
DJ Timmy Tim is an early stage name of Timothy Mosley, the influential American record producer and rapper better known as Timbaland.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: DJ Timmy Tim Target entity description: DJ Timmy Tim is an early stage name of Timothy Mosley, the influential American record producer and rapper better known as Timbaland.
-
A.
DJ Toomp
DJ Toomp is an American record producer and DJ best known for his influential work in Southern hip hop, including crafting hits for artists like T.I. and Kanye West.
-
B.
Dum Dum Dugan
Dum Dum Dugan is a gruff, mustachioed World War II-era soldier and close ally of Nick Fury in Marvel Comics, renowned for his combat skills and leadership within elite military units.
-
C.
Count von Count
Count von Count is a friendly, number-obsessed vampire Muppet who teaches children basic counting skills on the television show Sesame Street.
-
D.
Dandy Dan
Dandy Dan is the sharply dressed, ruthless mob boss antagonist in the 1976 musical gangster film "Bugsy Malone."
-
E.
Elvin
Elvin is a masculine given name most notably associated with Hall of Fame basketball player Elvin Hayes.
- 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_69aed934fbfc8190847068e4546de963 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef939d1308190930dc2c8272eafa4 |
completed | March 9, 2026, 4:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b533a80d4c8190bb1aac1b2900d9a8 |
completed | March 14, 2026, 10:08 a.m. |
| NEDg | Description generation | batch_69b5341fb74081909a33753e5fdd5c32 |
completed | March 14, 2026, 10:10 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b534d279548190bee44aea7828ed3b |
completed | March 14, 2026, 10:13 a.m. |
Created at: March 9, 2026, 3:30 p.m.