Triple
T20561886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jonathan Brandis |
E504861
|
entity |
| Predicate | appearedIn |
P795
|
FINISHED |
| Object | Ladybugs |
—
|
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: Ladybugs | Statement: [Jonathan Brandis, appearedIn, Ladybugs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ladybugs Context triple: [Jonathan Brandis, appearedIn, Ladybugs]
-
A.
Ladybugs
chosen
Ladybugs is a 1992 sports comedy film in which Jonathan Brandis plays a boy who disguises himself as a girl to help a struggling girls' soccer team.
-
B.
Ladybug
Ladybug is the unlucky but introspective assassin protagonist played by Brad Pitt in the 2022 action-comedy film "Bullet Train."
-
C.
Ladybird
Ladybird is a British children’s television series that follows the adventures of a small, friendly ladybird character in whimsical, educational stories.
-
D.
The Grouchy Ladybug
The Grouchy Ladybug is a popular children's picture book by Eric Carle that follows a bad-tempered ladybug learning about manners and sharing over the course of a day.
-
E.
Buzzy Beetle
Buzzy Beetle is a hard-shelled, fireproof enemy from the Super Mario series that typically walks along surfaces and retreats into its shell when jumped on.
- 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_69e0b4b6587c8190aee63dc7cff244ea |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a79ec10481909740eb6a08ae2658 |
completed | April 20, 2026, 10:24 p.m. |
Created at: April 16, 2026, 11:39 a.m.