Triple
T19545739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mae Murray |
E489041
|
entity |
| Predicate | causeOfCareerDecline |
P26452
|
FINISHED |
| Object | transition from silent films to sound films |
—
|
LITERAL 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: transition from silent films to sound films | Statement: [Mae Murray, causeOfCareerDecline, transition from silent films to sound films]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causeOfCareerDecline Context triple: [Mae Murray, causeOfCareerDecline, transition from silent films to sound films]
-
A.
hasIndustryDecline
Indicates that an entity is experiencing or associated with a reduction or downturn in its industry’s performance or activity.
-
B.
interpretationOfDecline
Indicates a relationship where one entity explains, characterizes, or provides a specific understanding of another entity’s decrease, deterioration, or downward trend.
-
C.
causeOfDownfall
chosen
Indicates a factor, event, or agent that brings about the failure, ruin, or collapse of someone or something.
-
D.
movementDecline
Indicates a reduction or worsening in the extent, frequency, or effectiveness of movement or mobility over time.
-
E.
managedCareerOf
Indicates that one entity was responsible for overseeing, directing, or handling the professional career of another entity.
- F. None of above.
Provenance (3 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_69d8e8db5b6c8190984b61f91981f575 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63876bacc8190b17e2087de679785 |
completed | April 20, 2026, 2:30 p.m. |
| PD | Predicate disambiguation | batch_69e514d4df3c8190b7e9b3b4fdf9452a |
completed | April 19, 2026, 5:45 p.m. |
Created at: April 10, 2026, 1:41 p.m.