Triple
T7419120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melissa Arnette Elliott |
E171199
|
entity |
| Predicate | associatedAct |
P37
|
FINISHED |
| Object | Magoo |
E402544
|
NE FINISHED |
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: Magoo | Statement: [Melissa Arnette Elliott, associatedAct, Magoo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Magoo Context triple: [Melissa Arnette Elliott, associatedAct, Magoo]
-
A.
Magoo
chosen
Magoo was an American rapper best known as one half of the hip hop duo Timbaland & Magoo, active in the late 1990s and early 2000s.
-
B.
Mr. Magoo
Mr. Magoo is a near-sighted, bumbling cartoon character known for getting into comical misadventures due to his poor vision.
-
C.
Moe
Moe is the nickname of Moe Berg, an American baseball player who famously served as a spy during World War II.
-
D.
Moe
Moe is a kangaroo character known by the name Moe.
-
E.
Quincy Magoo
Quincy Magoo is a classic cartoon character portrayed as a wealthy, stubborn, and extremely nearsighted older man whose visual impairments lead to humorous misadventures.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c68a625d048190af70eb8b63bec5a0 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f2e93ffc8190beb5a1d3eb6c5d23 |
completed | March 27, 2026, 9:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c81ef30ee88190a484f4b735913676 |
completed | March 28, 2026, 6:33 p.m. |
Created at: March 27, 2026, 3:11 p.m.