Triple
T7645941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evangeline (1919 film) |
E173119
|
entity |
| Predicate | protagonistOccupationOrRole |
P21567
|
FINISHED |
| Object | young Acadian woman |
—
|
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: young Acadian woman | Statement: [Evangeline (1919 film), protagonistOccupationOrRole, young Acadian woman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protagonistOccupationOrRole Context triple: [Evangeline (1919 film), protagonistOccupationOrRole, young Acadian woman]
-
A.
featuresProtagonistOccupation
chosen
Indicates that the work’s main character has a specified occupation or job role.
-
B.
protagonistDescription
Indicates that a text provides a descriptive summary or characterization of the story’s main protagonist.
-
C.
protagonistType
Indicates the role or category that the main character (protagonist) of a story or scenario belongs to.
-
D.
protagonistIs
Indicates that one entity serves as the main character or central figure in relation to another entity or narrative context.
-
E.
protagonistSocialStatus
Indicates the social standing or class position held by the story’s main character in relation to others in their society.
- 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_69c6995360188190968ee57b72a1627f |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6faf2aa1c8190945a691e46300ef2 |
completed | March 27, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e9ef1c81909c8bff716541ac1f |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:58 p.m.