Triple
T16292524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Late Late Show with Craig Ferguson |
E395559
|
entity |
| Predicate | sidekickType |
P48236
|
FINISHED |
| Object | robot skeleton |
—
|
LITERAL 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: robot skeleton | Statement: [The Late Late Show with Craig Ferguson, sidekickType, robot skeleton]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sidekickType Context triple: [The Late Late Show with Craig Ferguson, sidekickType, robot skeleton]
-
A.
formerSidekick
Indicates that one entity previously served as a sidekick or subordinate companion to another entity, but no longer holds that role.
-
B.
supportingCharacter
Indicates that one entity plays a secondary or assisting role in the story or context relative to another primary entity.
-
C.
secondaryProtagonistType
Indicates the role or category of a work’s secondary main character in relation to the primary protagonist.
-
D.
companionOf
Indicates that one entity serves as a companion or partner to another, typically accompanying or being closely associated with them.
-
E.
notableCompanionType
chosen
Indicates that one entity is a prominent or significant type of companion or associate in relation to another entity.
- F. None of above.
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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24919345881909ba4e7fe2e59340f |
completed | April 17, 2026, 2:52 p.m. |
| PD | Predicate disambiguation | batch_69e219f68d308190b71c1601303f0628 |
completed | April 17, 2026, 11:31 a.m. |
Created at: April 10, 2026, 5:05 a.m.