Triple
T1020097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minion Land |
E22019
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Gru |
E114480
|
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: Gru | Statement: [Minion Land, hasCharacter, Gru]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gru Context triple: [Minion Land, hasCharacter, Gru]
-
A.
Gru
chosen
Gru is the bald, long-nosed former supervillain and adoptive father of three girls who serves as the central protagonist of the Despicable Me animated film franchise.
-
B.
Grover
Grover is a masculine given name most famously borne by Grover Cleveland, the 22nd and 24th president of the United States.
-
C.
Geronimi
Geronimi is an Italian-origin surname most notably associated with Clyde Geronimi, a prominent animator and director for Walt Disney Studios.
-
D.
Elmer Fudd
Elmer Fudd is a classic Looney Tunes cartoon character best known as the bumbling, soft-spoken hunter perpetually chasing Bugs Bunny.
-
E.
Gus
Gus is the lovable, chubby mouse in Disney's 1950 animated film "Cinderella," known for his comic relief and loyal friendship to Cinderella.
- 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_69a493d6e380819097b384986ffc315c |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b7dbcf7c8190858b2d16a27bd2ff |
completed | March 1, 2026, 10:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac3bb423fc8190af65e94f8e2e75d0 |
completed | March 7, 2026, 2:52 p.m. |
Created at: March 1, 2026, 7:41 p.m.