Triple
T36165997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christmas Holiday |
E1045998
|
entity |
| Predicate | leadCharacterPlayedByGeneKelly |
P185046
|
FINISHED |
| Object | Robert Manette |
—
|
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: Robert Manette | Statement: [Christmas Holiday, leadCharacterPlayedByGeneKelly, Robert Manette]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadCharacterPlayedByGeneKelly Context triple: [Christmas Holiday, leadCharacterPlayedByGeneKelly, Robert Manette]
-
A.
leadCharacterPlayedByClarkGable
Indicates that the work’s lead character is portrayed by the actor Clark Gable.
-
B.
leadCharacterPlayedByDeannaDurbin
Indicates that the work’s lead character is portrayed by the actress Deanna Durbin.
-
C.
JudyGarlandRole
Indicates that a person held an acting role performed by Judy Garland in a specific work.
-
D.
hasGingerRogersRole
Indicates that an entity is assigned or associated with a role specifically identified as the "Ginger Rogers" role in a given context or production.
-
E.
leadCharacterPlayedByJeanHarlow
Indicates that the work’s lead character is portrayed by the actress Jean Harlow.
- 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_69f76e396bc88190b99d221bff9be27a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7bb1d6b70819091227bd011734d19 |
completed | May 3, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a4aad48190a62e41c5e39339d9 |
completed | May 3, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69f7ba6c27e081908868a2b50d1d603c |
completed | May 3, 2026, 9:13 p.m. |
Created at: May 3, 2026, 4:08 p.m.