Triple
T9465993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Late Night |
E228270
|
entity |
| Predicate | hasSpinOffHostCareer |
P89100
|
FINISHED |
| Object | David Letterman on CBS |
—
|
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: David Letterman on CBS | Statement: [Late Night, hasSpinOffHostCareer, David Letterman on CBS]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpinOffHostCareer Context triple: [Late Night, hasSpinOffHostCareer, David Letterman on CBS]
-
A.
hasSpinOff
Indicates that one entity is a derivative or spin-off product, work, or organization that originated from another entity.
-
B.
portrayedByInSpinOff
Indicates that an entity is portrayed by a particular actor specifically in a spin-off production related to the original work.
-
C.
spinoffAppearance
Indicates that an entity appears in a derivative or spinoff work related to another original work or series.
-
D.
spinOffCharacter
Indicates that one character originates as a derivative or secondary creation from another, typically branching off into its own distinct narrative or work.
-
E.
hasFranchiseOrSpinOff
Indicates that one work, series, or product is related to another as a franchise entry or a spin-off derived from it.
- F. None of above. chosen
Provenance (4 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_69ca846fee388190a6ec273fd644b88b |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7fdc08f08190ad17de08d2c2eca2 |
completed | April 1, 2026, 8:28 p.m. |
| PD | Predicate disambiguation | batch_69cca55caaa8819089c5138e014892d3 |
completed | April 1, 2026, 4:55 a.m. |
| PDg | Predicate description generation | batch_69ccbf9b080c819098934a18cf2bac5d |
completed | April 1, 2026, 6:47 a.m. |
Created at: March 30, 2026, 7:53 p.m.