Triple
T37150964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kissing a Fool |
E920359
|
entity |
| Predicate | hasNotableWorkOfActress |
P61425
|
FINISHED |
| Object | Cara Buono |
E268545
|
NE 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: Cara Buono | Statement: [Kissing a Fool, hasNotableWorkOfActress, Cara Buono]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableWorkOfActress Context triple: [Kissing a Fool, hasNotableWorkOfActress, Cara Buono]
-
A.
hasAssociatedActress
Indicates that an entity is linked to an actress who is associated with it in a relevant context (e.g., participation, representation, or involvement).
-
B.
hasNotableFilm
Indicates that an entity is associated with a film that is considered significant, well-known, or particularly noteworthy.
-
C.
hasNotableWorkExample
chosen
Indicates that an entity has a specific notable work cited as an example associated with it.
-
D.
hasNotableAuthorWork
Indicates that an author is notably associated with creating a particular work.
-
E.
hasArtistOfNotableWork
Indicates that an entity is associated with the artist who created a notable work related to that entity.
- F. None of above.
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_69f76e9f87c08190b4c8f7fafbd8345a |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a406376d4f08190baf8d1e368818760 |
completed | June 27, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_6a037a11efc08190bb7cacc1325b4dc6 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:15 p.m.