Triple
T26635079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen Kelly |
E668612
|
entity |
| Predicate | characterPortrayedByGloriaSwanson |
P178580
|
FINISHED |
| Object | Kitty Kelly |
—
|
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: Kitty Kelly | Statement: [Queen Kelly, characterPortrayedByGloriaSwanson, Kitty Kelly]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterPortrayedByGloriaSwanson Context triple: [Queen Kelly, characterPortrayedByGloriaSwanson, Kitty Kelly]
-
A.
starGloriaSwansonLaterAppearedIn
Indicates that Gloria Swanson, who starred in a work, later appeared in another related work.
-
B.
barbaraStanwyckRole
Indicates that the subject is a role or character portrayed by Barbara Stanwyck.
-
C.
MarilynMonroeRoleType
Indicates the type or category of role associated with Marilyn Monroe in a given context.
-
D.
MaryAstorRole
Indicates that an entity represents a role or character portrayed by Mary Astor in a film, play, or other performance.
-
E.
hasMarleneDietrichRoleType
Indicates that an entity has a specific type or category of role associated with Marlene Dietrich.
- 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_69ee9d0024b8819090a7c8cf669a3b6c |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f7117e55908190a67105e92bc4830f |
completed | May 3, 2026, 9:12 a.m. |
| PD | Predicate disambiguation | batch_69f70f380690819090cc34763ba460ed |
completed | May 3, 2026, 9:02 a.m. |
| PDg | Predicate description generation | batch_69f7117cf2188190b29e36fc1e342c60 |
completed | May 3, 2026, 9:12 a.m. |
Created at: April 27, 2026, 2:26 a.m.