Triple
T24200724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrs. Paddy |
E599968
|
entity |
| Predicate | isOftenPortrayedBy |
P18297
|
FINISHED |
| Object | stage actresses in community theatre |
—
|
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: stage actresses in community theatre | Statement: [Mrs. Paddy, isOftenPortrayedBy, stage actresses in community theatre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOftenPortrayedBy Context triple: [Mrs. Paddy, isOftenPortrayedBy, stage actresses in community theatre]
-
A.
oftenDepictedAs
chosen
Indicates that one entity is frequently represented or portrayed in the form, appearance, or symbolism of another entity.
-
B.
occasionallyPortrayedAs
Indicates that one entity is sometimes depicted or represented as another entity, but not consistently or as its primary form.
-
C.
wasPortrayedAs
Indicates that one entity has been depicted or represented in the form or role of another entity, typically within some medium or context.
-
D.
commonlyDepictedOn
Indicates that something is frequently shown or represented on the surface, medium, or context of another thing.
-
E.
workOftenDepicts
Indicates that one entity’s work frequently portrays, represents, or includes the other entity as a subject or theme.
- 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_69e288ceaab88190899d0acb5931591d |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f27ca08874819081dd6613ac462c40 |
completed | April 29, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f1c43e55688190b55fc20274ed471c |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 17, 2026, 11:36 p.m.