Triple
T36867654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emma Lucretia Dobbin |
E911128
|
entity |
| Predicate | genreOfRelative |
P186601
|
FINISHED |
| Object | Gothic fiction |
—
|
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: Gothic fiction | Statement: [Emma Lucretia Dobbin, genreOfRelative, Gothic fiction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfRelative Context triple: [Emma Lucretia Dobbin, genreOfRelative, Gothic fiction]
-
A.
genreOfPerson
Indicates that a person is associated with or specializes in a particular genre (such as a style, category, or type of creative work).
-
B.
genreOfAssociatedPerson
Indicates that a particular genre is associated with a given person, such as an artist, author, or performer.
-
C.
genreRelation
Indicates a relationship where one entity is categorized as having, belonging to, or being associated with a particular genre defined by another entity.
-
D.
genreAssociatedViaFamily
Indicates that a genre is connected to another entity through a familial or family-based relationship rather than a direct or primary association.
-
E.
genreOfCharacter
Indicates that a character belongs to or is associated with a particular genre (such as fantasy, horror, or comedy).
- 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_69f76e80f6f0819091cba8e19b269615 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f9fe1a1ca4819084c196f0041f0be2 |
completed | May 5, 2026, 2:26 p.m. |
| PD | Predicate disambiguation | batch_69f7cf7890008190a8bc355ff2d61c86 |
completed | May 3, 2026, 10:43 p.m. |
| PDg | Predicate description generation | batch_69f9fd66eed48190bdc26a8def328c2d |
completed | May 5, 2026, 2:23 p.m. |
Created at: May 3, 2026, 4:13 p.m.