Triple
T11386079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tiny Toon Adventures |
E269717
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object |
Gogo Dodo
Gogo Dodo is a zany, surreal cartoon character from the Tiny Toon Adventures series, known for his reality-bending antics and residence in the bizarre world of Wackyland.
|
E922960
|
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: Gogo Dodo | Statement: [Tiny Toon Adventures, featuresCharacter, Gogo Dodo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gogo Dodo Context triple: [Tiny Toon Adventures, featuresCharacter, Gogo Dodo]
-
A.
Gogo Penguin
GoGo Penguin is a British contemporary jazz trio from Manchester known for blending acoustic jazz instrumentation with electronic, minimalist, and dance music influences.
-
B.
Doo-Dah
Doo-Dah is a quirky, affectionate nickname used by locals to refer to the city of Wichita, Kansas.
-
C.
Kokovoko
Kokovoko is the fictional, remote South Pacific island homeland of Queequeg in Herman Melville’s novel "Moby-Dick."
-
D.
Gogo
Gogo is an in-flight internet service provider known for supplying Wi-Fi connectivity on commercial airlines.
-
E.
Doozer
Doozer is a television production company founded by Bill Lawrence, best known for producing series such as Scrubs, Cougar Town, and Ted Lasso.
- 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: Gogo Dodo Triple: [Tiny Toon Adventures, featuresCharacter, Gogo Dodo]
Generated description
Gogo Dodo is a zany, surreal cartoon character from the Tiny Toon Adventures series, known for his reality-bending antics and residence in the bizarre world of Wackyland.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gogo Dodo Target entity description: Gogo Dodo is a zany, surreal cartoon character from the Tiny Toon Adventures series, known for his reality-bending antics and residence in the bizarre world of Wackyland.
-
A.
Gogo Penguin
GoGo Penguin is a British contemporary jazz trio from Manchester known for blending acoustic jazz instrumentation with electronic, minimalist, and dance music influences.
-
B.
Doo-Dah
Doo-Dah is a quirky, affectionate nickname used by locals to refer to the city of Wichita, Kansas.
-
C.
Kokovoko
Kokovoko is the fictional, remote South Pacific island homeland of Queequeg in Herman Melville’s novel "Moby-Dick."
-
D.
Gogo
Gogo is an in-flight internet service provider known for supplying Wi-Fi connectivity on commercial airlines.
-
E.
Doozer
Doozer is a television production company founded by Bill Lawrence, best known for producing series such as Scrubs, Cougar Town, and Ted Lasso.
- 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_69d6aacdbc6c8190af6dc3d5f5d22836 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7fc378d808190b587a044ede67e1e |
completed | April 9, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e58c3c9a7081908002d726ec9e7715 |
completed | April 20, 2026, 2:15 a.m. |
| NEDg | Description generation | batch_69e5932d3cb88190807acdcdc3aaa9fc |
completed | April 20, 2026, 2:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e59a0ab7e081908cb8761c4f82c664 |
completed | April 20, 2026, 3:14 a.m. |
Created at: April 8, 2026, 9:34 p.m.