Triple
T20818304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dave Goelz |
E512503
|
entity |
| Predicate | notableCharacter |
P1481
|
FINISHED |
| Object | Gonzo the Great |
—
|
NE NERFINISHED |
How this triple was built (2 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: Gonzo the Great | Statement: [Dave Goelz, notableCharacter, Gonzo the Great]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gonzo the Great Context triple: [Dave Goelz, notableCharacter, Gonzo the Great]
-
A.
Gonzo the Great
chosen
Gonzo the Great is a daredevil, eccentric blue Muppet known for his bizarre stunts and offbeat sense of humor in The Muppet Show franchise.
-
B.
Gonzo
Gonzo is a high-altitude Gulfstream IV-SP jet operated by NOAA for atmospheric research and hurricane reconnaissance missions.
-
C.
Gonzo
Gonzo is a Japanese animation studio known for producing a wide range of anime series and films, often featuring distinctive visual styles and experimental storytelling.
-
D.
Dr. Gonzo
Dr. Gonzo is a high-energy electro-house track by Italian DJ duo Crookers, known for its heavy bass, distorted synths, and club-oriented sound.
-
E.
Dr. Gonzo
Dr. Gonzo is the wild, unpredictable attorney and drug-fueled companion of Raoul Duke in Hunter S. Thompson’s "Fear and Loathing in Las Vegas."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4cd25088190b48ca9700cd24efc |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2f5b1e08190a9c26f76bd544b68 |
completed | April 21, 2026, 12:21 a.m. |
Created at: April 16, 2026, 12:41 p.m.