Triple
T18801138
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Booger McFarland |
E459753
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object |
Booger
Booger is the nickname of Anthony "Booger" McFarland, a former NFL defensive tackle and current American football analyst and commentator.
|
E1342491
|
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: Booger | Statement: [Booger McFarland, nickname, Booger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Booger Context triple: [Booger McFarland, nickname, Booger]
-
A.
Goober
Goober is a fictional, affable and goofy auto mechanic character from the classic American television series "The Andy Griffith Show" and its spin-offs.
-
B.
Snot
Snot is a fictional character from the animated television series "American Dad!", known as Steve Smith’s nerdy and often awkward best friend.
-
C.
Snot
Snot is an American hardcore punk and nu metal band known for its aggressive sound and fusion of punk, metal, and funk elements.
-
D.
Stinkie
Stinkie is one of the mischievous Ghostly Trio in the 1995 live-action film "Casper," known for his crude humor and prankster personality.
-
E.
Gooigi
Gooigi is a green, goo-like doppelgänger of Luigi from the Luigi’s Mansion series, used as a playable helper character to solve puzzles and reach otherwise inaccessible areas.
- 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: Booger Triple: [Booger McFarland, nickname, Booger]
Generated description
Booger is the nickname of Anthony "Booger" McFarland, a former NFL defensive tackle and current American football analyst and commentator.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Booger Target entity description: Booger is the nickname of Anthony "Booger" McFarland, a former NFL defensive tackle and current American football analyst and commentator.
-
A.
Goober
Goober is a fictional, affable and goofy auto mechanic character from the classic American television series "The Andy Griffith Show" and its spin-offs.
-
B.
Snot
Snot is a fictional character from the animated television series "American Dad!", known as Steve Smith’s nerdy and often awkward best friend.
-
C.
Snot
Snot is an American hardcore punk and nu metal band known for its aggressive sound and fusion of punk, metal, and funk elements.
-
D.
Stinkie
Stinkie is one of the mischievous Ghostly Trio in the 1995 live-action film "Casper," known for his crude humor and prankster personality.
-
E.
Gooigi
Gooigi is a green, goo-like doppelgänger of Luigi from the Luigi’s Mansion series, used as a playable helper character to solve puzzles and reach otherwise inaccessible areas.
- 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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a02332d88190b68feea7f2f86d06 |
completed | April 20, 2026, 3:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a054723def4819097961a04087a54a3 |
completed | May 14, 2026, 3:53 a.m. |
| NEDg | Description generation | batch_6a0549358ba081909eb649898d1b3a8a |
completed | May 14, 2026, 4:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0549c825f481909d2da63688b36186 |
completed | May 14, 2026, 4:04 a.m. |
Created at: April 10, 2026, 11:53 a.m.