Triple
T35149001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Bishop’s Wife |
E1014930
|
entity |
| Predicate | CaryGrantRole |
P182332
|
FINISHED |
| Object | Dudley |
—
|
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: Dudley | Statement: [The Bishop’s Wife, CaryGrantRole, Dudley]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: CaryGrantRole Context triple: [The Bishop’s Wife, CaryGrantRole, Dudley]
-
A.
humphreyBogartRole
Indicates that one entity is a role or character portrayed by Humphrey Bogart in a film, play, or other performance.
-
B.
leadCharacterPlayedByClarkGable
Indicates that the work’s lead character is portrayed by the actor Clark Gable.
-
C.
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.
-
D.
barbaraStanwyckRole
Indicates that the subject is a role or character portrayed by Barbara Stanwyck.
-
E.
hasRitaHayworthRole
Indicates that an entity has a role or character associated with Rita Hayworth, such as portraying her or a role closely linked to her.
- 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_69f76dda7c108190a2ffd93eb6c341a7 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78cea708c8190a2702c9825b6b094 |
completed | May 3, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69f78b9106008190930b3b3675b737d6 |
completed | May 3, 2026, 5:53 p.m. |
| PDg | Predicate description generation | batch_69f78c337cec8190bfdab225a3cc96db |
completed | May 3, 2026, 5:56 p.m. |
Created at: May 3, 2026, 4:02 p.m.