Triple
T20177624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jason "Wee Man" Acuña |
E492641
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object |
Wee Man
Wee Man is a skateboarder, stunt performer, and television personality best known as a prominent cast member of the Jackass franchise.
|
E1416700
|
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: Wee Man | Statement: [Jason "Wee Man" Acuña, nickname, Wee Man]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wee Man Context triple: [Jason "Wee Man" Acuña, nickname, Wee Man]
-
A.
Little Man
"Little Man" is a stand-up comedy special by American comedian Gary Owen, showcasing his energetic storytelling and observational humor.
-
B.
Little Man
Little Man is a 2006 American comedy film starring Marlon Wayans as a diminutive criminal who poses as a baby to retrieve a stolen diamond.
-
C.
Little Man
Little Man is a prominent subsidiary summit of Skiddaw in England’s Lake District, popular with hikers for its fine views and distinctive profile.
-
D.
Little Man
"Little Man" is a 1966 pop song by the American duo Sonny & Cher, known for its distinctive folk-influenced sound and international chart success.
-
E.
Raggedy Man
Raggedy Man is a 1981 American drama film, starring Sissy Spacek and Eric Roberts, about a divorced telephone operator in a small Texas town during World War II.
- 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: Wee Man Triple: [Jason "Wee Man" Acuña, nickname, Wee Man]
Generated description
Wee Man is a skateboarder, stunt performer, and television personality best known as a prominent cast member of the Jackass franchise.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wee Man Target entity description: Wee Man is a skateboarder, stunt performer, and television personality best known as a prominent cast member of the Jackass franchise.
-
A.
Little Man
"Little Man" is a stand-up comedy special by American comedian Gary Owen, showcasing his energetic storytelling and observational humor.
-
B.
Little Man
Little Man is a 2006 American comedy film starring Marlon Wayans as a diminutive criminal who poses as a baby to retrieve a stolen diamond.
-
C.
Little Man
"Little Man" is a 1966 pop song by the American duo Sonny & Cher, known for its distinctive folk-influenced sound and international chart success.
-
D.
Little Man
Little Man is a prominent subsidiary summit of Skiddaw in England’s Lake District, popular with hikers for its fine views and distinctive profile.
-
E.
Raggedy Man
Raggedy Man is a 1981 American drama film, starring Sissy Spacek and Eric Roberts, about a divorced telephone operator in a small Texas town during World War II.
- 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e668ec4d7c81909fa4bdc58ed54aeb |
completed | April 20, 2026, 5:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a083c79d2948190a1df0d3bd1f9c6ad |
completed | May 16, 2026, 9:44 a.m. |
| NEDg | Description generation | batch_6a083d86085c8190a71d0dce65c659a4 |
completed | May 16, 2026, 9:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a083eb380f48190bda8549d122f830b |
completed | May 16, 2026, 9:53 a.m. |
Created at: April 11, 2026, 11:36 p.m.