Triple
T23389604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lotso |
E593975
|
entity |
| Predicate | fullName |
P16
|
FINISHED |
| Object | Lots-O'-Huggin' Bear |
—
|
NE NERFINISHED |
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: Lots-O'-Huggin' Bear | Statement: [Lotso, fullName, Lots-O'-Huggin' Bear]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lots-O'-Huggin' Bear Context triple: [Lotso, fullName, Lots-O'-Huggin' Bear]
-
A.
Lots-o'-Huggin' Bear
chosen
Lots-o'-Huggin' Bear is the strawberry-scented, pink teddy bear and main antagonist from Pixar's film "Toy Story 3."
-
B.
The Teddy Bears
The Teddy Bears were a late-1950s American pop vocal group best known for their hit single "To Know Him Is to Love Him," produced and written by Phil Spector.
-
C.
The Wild Things
The Wild Things is a novel by Dave Eggers that reimagines and expands upon Maurice Sendak’s classic children’s book Where the Wild Things Are.
-
D.
Bde Maka Ska
Bde Maka Ska is the largest lake in Minneapolis, Minnesota, popular for recreation and known as part of the city’s Chain of Lakes.
-
E.
Raggedy Man
Raggedy Man is a 1981 American drama film, starring Sissy Spacek and Eric Roberts, about a divorced telephone operator in a small Texas town during World War II.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e25d2754fc819085deea939bde60ab |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a49a7c14819082aab826715976c5 |
completed | April 29, 2026, 6:26 a.m. |
Created at: April 17, 2026, 5:35 p.m.