Triple
T8154238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baldrick |
E190405
|
entity |
| Predicate | associatedWithCatchphrase |
P74838
|
FINISHED |
| Object | I have a cunning plan |
—
|
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: I have a cunning plan | Statement: [Baldrick, associatedWithCatchphrase, I have a cunning plan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithCatchphrase Context triple: [Baldrick, associatedWithCatchphrase, I have a cunning plan]
-
A.
associatedWithFamousSlogan
Indicates that an entity is connected to, known for, or commonly linked with a particular famous slogan.
-
B.
featuresCatchphrase
Indicates that an entity prominently includes or is associated with a particular catchphrase.
-
C.
characterCatchphrase
chosen
Indicates that a particular phrase is commonly and distinctively used by a character as their catchphrase.
-
D.
associatedWithAnecdote
Indicates a relationship where something is linked or connected to a particular anecdote, such as being based on, derived from, or exemplified by that anecdotal account.
-
E.
usedPhrase
Indicates that one entity employed or expressed a particular phrase in speech, writing, or another form of communication.
- 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_69ca82bfeb6481909d07b91b5cf69f59 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb44d566b08190a6bb672f9c368806 |
completed | March 31, 2026, 3:51 a.m. |
| PD | Predicate disambiguation | batch_69cb36a0847c8190af9038aef78319b3 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:37 p.m.