Triple
T32303215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Yellow Wallpaper |
E825290
|
entity |
| Predicate | characterRoleOfJohn |
P23263
|
FINISHED |
| Object | husband of the narrator |
—
|
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: husband of the narrator | Statement: [The Yellow Wallpaper, characterRoleOfJohn, husband of the narrator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterRoleOfJohn Context triple: [The Yellow Wallpaper, characterRoleOfJohn, husband of the narrator]
-
A.
leadActorForCharacter_John Person
Indicates that John Person is the primary actor portraying a specific character.
-
B.
roleOfJohnWilliamson
Indicates that an entity serves in the role or capacity associated with John Williamson.
-
C.
describesCharacterRole
Indicates that one entity specifies or defines the narrative or functional role played by another entity.
-
D.
roleOfJohnHurt
Indicates the specific role or character that John Hurt portrays or assumes in a given context.
-
E.
featuresCharacterRole
chosen
Indicates that a work includes a character appearing in a specific narrative or functional role.
- 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_69f349115304819084ee91d345b6c8aa |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fed83b1d188190a318b0ad3003200a |
completed | May 9, 2026, 6:46 a.m. |
| PD | Predicate disambiguation | batch_69fed78e03548190b6e6ad93ae8d131d |
completed | May 9, 2026, 6:43 a.m. |
Created at: May 1, 2026, 12:45 a.m.