Triple
T6362362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agnes Ayres as Lady Diana Mayo |
E143140
|
entity |
| Predicate | targetAudienceEra |
P70204
|
FINISHED |
| Object | 1920s American filmgoers |
—
|
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: 1920s American filmgoers | Statement: [Agnes Ayres as Lady Diana Mayo, targetAudienceEra, 1920s American filmgoers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetAudienceEra Context triple: [Agnes Ayres as Lady Diana Mayo, targetAudienceEra, 1920s American filmgoers]
-
A.
appliesToEra
Indicates that something is relevant, valid, or in effect during a particular historical or temporal era.
-
B.
discoveryEra
Indicates the historical period or era during which the entity was discovered or first identified.
-
C.
partOfEra
Indicates that one entity exists as a temporal segment or component within the duration or scope of a larger historical era.
-
D.
studentEra
Indicates a time period during which an individual holds the status or role of a student.
-
E.
typicalAudience
Indicates the group of people for whom something (such as a work, product, or resource) is primarily intended or most suitable.
- 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_69c008d7a9c4819098d647ec47776917 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0680c02b481908618317566e31a5c |
completed | March 22, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69c060ec091c8190912aac44e1b8b1c9 |
completed | March 22, 2026, 9:36 p.m. |
| PDg | Predicate description generation | batch_69c0623bb29081908bfdfb84a07ece90 |
completed | March 22, 2026, 9:42 p.m. |
Created at: March 22, 2026, 4:32 p.m.