Triple
T14253467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Go Jetters |
E353326
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object |
Ubercorn
Ubercorn is a funky, disco-loving unicorn and mentor figure who guides the Go Jetters on their educational adventures around the world.
|
E1089673
|
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: Ubercorn | Statement: [Go Jetters, featuresCharacter, Ubercorn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ubercorn Context triple: [Go Jetters, featuresCharacter, Ubercorn]
-
A.
Le Crunch
Le Crunch is the intense and historic rugby union rivalry between the national teams of France and England.
-
B.
Grabler
Grabler is a surname of likely Germanic origin associated with individuals such as Maria Magdalena Grabler.
-
C.
Pizzafari
Pizzafari is a quick-service, pizza-focused restaurant located on Discovery Island in Disney's Animal Kingdom theme park.
-
D.
Beyond Burger
Beyond Burger is a popular plant-based burger patty designed to closely mimic the taste and texture of beef while being made entirely from non-animal ingredients.
-
E.
Chomps
Chomps is a dog-themed mascot character for the NFL’s Cleveland Browns, typically depicted as a muscular, anthropomorphic brown dog in team gear.
- 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: Ubercorn Triple: [Go Jetters, featuresCharacter, Ubercorn]
Generated description
Ubercorn is a funky, disco-loving unicorn and mentor figure who guides the Go Jetters on their educational adventures around the world.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ubercorn Target entity description: Ubercorn is a funky, disco-loving unicorn and mentor figure who guides the Go Jetters on their educational adventures around the world.
-
A.
Le Crunch
Le Crunch is the intense and historic rugby union rivalry between the national teams of France and England.
-
B.
Grabler
Grabler is a surname of likely Germanic origin associated with individuals such as Maria Magdalena Grabler.
-
C.
Pizzafari
Pizzafari is a quick-service, pizza-focused restaurant located on Discovery Island in Disney's Animal Kingdom theme park.
-
D.
Beyond Burger
Beyond Burger is a popular plant-based burger patty designed to closely mimic the taste and texture of beef while being made entirely from non-animal ingredients.
-
E.
Chomps
Chomps is a dog-themed mascot character for the NFL’s Cleveland Browns, typically depicted as a muscular, anthropomorphic brown dog in team gear.
- 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_69d8278c43e08190824146f4632b89a5 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6297f38c819090d7c7fd8bfa2e9e |
completed | April 14, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd325c98288190ba035fb5cc5bcf6b |
completed | May 8, 2026, 12:46 a.m. |
| NEDg | Description generation | batch_69fd33cba18481908f2dfe358017f11b |
completed | May 8, 2026, 12:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd346ffb9c81909ec28e514ea5451b |
completed | May 8, 2026, 12:55 a.m. |
Created at: April 10, 2026, 1:09 a.m.