Triple
T31230276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Bribe |
E796260
|
entity |
| Predicate | characterPlayedBy Charles Laughton |
P196547
|
FINISHED |
| Object | J. J. Bealer |
—
|
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: J. J. Bealer | Statement: [The Bribe, characterPlayedBy Charles Laughton, J. J. Bealer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterPlayedBy Charles Laughton Context triple: [The Bribe, characterPlayedBy Charles Laughton, J. J. Bealer]
-
A.
characterPlayedBy Charles Hawtrey
Indicates that a given character is portrayed or acted by Charles Hawtrey.
-
B.
characterPlayedBy Robert Taylor
Indicates that a given character is portrayed or acted by Robert Taylor.
-
C.
characterPlayedByRichardHarris
Indicates that the subject is a character that was portrayed by the actor Richard Harris.
-
D.
characterPlayedBy Kenneth Connor
Indicates that a character is portrayed or acted by Kenneth Connor.
-
E.
leadCharacterPlayedByClarkGable
Indicates that the work’s lead character is portrayed by the actor Clark Gable.
- 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_69f224da98f88190ab32f690cce5d303 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe5c1a502081909d4024e514309c8e |
completed | May 8, 2026, 9:56 p.m. |
| PD | Predicate disambiguation | batch_69fe5a9df21c819087153f5d0bcaa987 |
completed | May 8, 2026, 9:50 p.m. |
| PDg | Predicate description generation | batch_69fe5c196f4081908f150d4cd6c528fa |
completed | May 8, 2026, 9:56 p.m. |
Created at: April 29, 2026, 9:10 p.m.