Triple
T25050800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Eliot’s Life as Related in Her Letters and Journals |
E627371
|
entity |
| Predicate | biographicalSubjectOccupation |
P85131
|
FINISHED |
| Object | novelist |
—
|
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: novelist | Statement: [George Eliot’s Life as Related in Her Letters and Journals, biographicalSubjectOccupation, novelist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: biographicalSubjectOccupation Context triple: [George Eliot’s Life as Related in Her Letters and Journals, biographicalSubjectOccupation, novelist]
-
A.
hasBiographicalSubjectOccupation
chosen
Indicates that the biographical subject is or was engaged in the specified occupation or profession.
-
B.
isBiographerOf
Indicates that one person has written a biography about another person.
-
C.
namedPersonOccupation
Indicates that a person is explicitly identified as having a particular occupation or job role.
-
D.
biographicalSubjectStageName
Indicates that the object is the stage name used by the biographical subject referenced by the subject.
-
E.
authorOccupation
Indicates the professional role or job that an author holds or is associated with.
- 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_69e2ff2b4c80819087c916b2b16241b9 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f454a200f481908bceaca32cd1d775 |
completed | May 1, 2026, 7:22 a.m. |
| PD | Predicate disambiguation | batch_69f442c861188190967655c6d8012380 |
completed | May 1, 2026, 6:06 a.m. |
Created at: April 18, 2026, 6:09 a.m.