Triple
T13109375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brickleberry |
E310930
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Connie Cunaman
Connie Cunaman is a muscular, socially awkward, and often unhinged park ranger from the animated comedy series "Brickleberry."
|
E1021497
|
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: Connie Cunaman | Statement: [Brickleberry, mainCharacter, Connie Cunaman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Connie Cunaman Context triple: [Brickleberry, mainCharacter, Connie Cunaman]
-
A.
Connie D'Amico
Connie D'Amico is a recurring character on the animated TV show Family Guy, known as the popular yet mean-spirited girl at James Woods Regional High School.
-
B.
Connie Morgan
Connie Morgan was a pioneering female second baseman in Negro league baseball, best known for playing with the Indianapolis Clowns in the 1950s.
-
C.
Connie Nickerson
Connie Nickerson was the wife of American actor and comedian Eddie Bracken.
-
D.
Dana Congdon
Dana Congdon is a film editor best known for his work on movies such as the anthology comedy "Four Rooms."
-
E.
Connie Codarini
Connie Codarini was a founding member and bass singer of the Canadian vocal group The Four Lads, known for their popular hits in the 1950s.
- 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: Connie Cunaman Triple: [Brickleberry, mainCharacter, Connie Cunaman]
Generated description
Connie Cunaman is a muscular, socially awkward, and often unhinged park ranger from the animated comedy series "Brickleberry."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Connie Cunaman Target entity description: Connie Cunaman is a muscular, socially awkward, and often unhinged park ranger from the animated comedy series "Brickleberry."
-
A.
Connie D'Amico
Connie D'Amico is a recurring character on the animated TV show Family Guy, known as the popular yet mean-spirited girl at James Woods Regional High School.
-
B.
Connie Morgan
Connie Morgan was a pioneering female second baseman in Negro league baseball, best known for playing with the Indianapolis Clowns in the 1950s.
-
C.
Connie Nickerson
Connie Nickerson was the wife of American actor and comedian Eddie Bracken.
-
D.
Dana Congdon
Dana Congdon is a film editor best known for his work on movies such as the anthology comedy "Four Rooms."
-
E.
Connie Codarini
Connie Codarini was a founding member and bass singer of the Canadian vocal group The Four Lads, known for their popular hits in the 1950s.
- 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_69d806a872d08190a329806f8ff30df4 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9817ce07881909ec552bf861ac175 |
completed | April 10, 2026, 11:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6e27bd8fc8190a81130b7cb3a8bd8 |
completed | May 3, 2026, 5:51 a.m. |
| NEDg | Description generation | batch_69f6e37023d48190ba6a0b790ed23370 |
completed | May 3, 2026, 5:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6e407dd988190b928b8931985a815 |
completed | May 3, 2026, 5:58 a.m. |
Created at: April 9, 2026, 9:05 p.m.