Triple
T37391162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miss Margarida’s Way |
E928711
|
entity |
| Predicate | characterRoleOfMissMargarida |
P192169
|
FINISHED |
| Object | authoritarian teacher |
—
|
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: authoritarian teacher | Statement: [Miss Margarida’s Way, characterRoleOfMissMargarida, authoritarian teacher]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterRoleOfMissMargarida Context triple: [Miss Margarida’s Way, characterRoleOfMissMargarida, authoritarian teacher]
-
A.
MaryAstorRole
Indicates that an entity represents a role or character portrayed by Mary Astor in a film, play, or other performance.
-
B.
describesCharacterRole
chosen
Indicates that one entity specifies or defines the narrative or functional role played by another entity.
-
C.
roleOfDellaStreetPlayedBy
Indicates that a specified actor portrays the character Della Street in a performance or production.
-
D.
characterPortrayedByRuthGordon
Indicates that a given character is portrayed or played by the actress Ruth Gordon.
-
E.
motherCharacterName
Indicates that one character is the mother of another character, specifying a maternal parent-child relationship between them.
- 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_69f76ebb10c481909b54b9dba263e29f |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fff09dae088190bd8460060d778feb |
completed | May 10, 2026, 2:42 a.m. |
| PD | Predicate disambiguation | batch_69fff0027c5c8190baa5c7a15852cbe0 |
completed | May 10, 2026, 2:40 a.m. |
Created at: May 3, 2026, 4:16 p.m.