Triple
T19201395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love Tractor |
E470115
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object |
Buzzy Beamer
Buzzy Beamer is a musician best known as a member of the Athens, Georgia-based alternative rock band Love Tractor.
|
E1364043
|
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: Buzzy Beamer | Statement: [Love Tractor, hasMember, Buzzy Beamer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Buzzy Beamer Context triple: [Love Tractor, hasMember, Buzzy Beamer]
-
A.
Dr. Beeper
Dr. Beeper is a pompous, uptight physician character from the golf comedy film "Caddyshack," known for his membership at the exclusive Bushwood Country Club.
-
B.
Buzzy Beetle
Buzzy Beetle is a hard-shelled, fireproof enemy from the Super Mario series that typically walks along surfaces and retreats into its shell when jumped on.
-
C.
Little Beeper
Little Beeper is a roadrunner-style cartoon character from the animated series Tiny Toon Adventures, known for his incredible speed and slapstick chases.
-
D.
Buzz the Bee
Buzz the Bee is the cheerful cartoon bee mascot featured on Stinger’s branding and promotional materials.
-
E.
Buster Beetle
Buster Beetle is a recurring enemy in the Super Mario series known for picking up and throwing ice blocks at the player.
- 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: Buzzy Beamer Triple: [Love Tractor, hasMember, Buzzy Beamer]
Generated description
Buzzy Beamer is a musician best known as a member of the Athens, Georgia-based alternative rock band Love Tractor.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Buzzy Beamer Target entity description: Buzzy Beamer is a musician best known as a member of the Athens, Georgia-based alternative rock band Love Tractor.
-
A.
Dr. Beeper
Dr. Beeper is a pompous, uptight physician character from the golf comedy film "Caddyshack," known for his membership at the exclusive Bushwood Country Club.
-
B.
Buzzy Beetle
Buzzy Beetle is a hard-shelled, fireproof enemy from the Super Mario series that typically walks along surfaces and retreats into its shell when jumped on.
-
C.
Little Beeper
Little Beeper is a roadrunner-style cartoon character from the animated series Tiny Toon Adventures, known for his incredible speed and slapstick chases.
-
D.
Buzz the Bee
Buzz the Bee is the cheerful cartoon bee mascot featured on Stinger’s branding and promotional materials.
-
E.
Buster Beetle
Buster Beetle is a recurring enemy in the Super Mario series known for picking up and throwing ice blocks at the player.
- 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_69d8dd0ad9088190a173b32657ae2e7a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f9991ba48190ab92805daec3877b |
completed | April 20, 2026, 10:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0700dc26648190ae58baddc8754ba0 |
completed | May 15, 2026, 11:17 a.m. |
| NEDg | Description generation | batch_6a070191a48481908f2c731d0d1d00bf |
completed | May 15, 2026, 11:20 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07025e91488190a25f6eb4fd6916c2 |
completed | May 15, 2026, 11:24 a.m. |
Created at: April 10, 2026, 12:07 p.m.