Triple
T8876797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Shelley |
E211305
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Falkner |
E163123
|
NE 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: Falkner | Statement: [Mary Shelley, notableWork, Falkner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Falkner Context triple: [Mary Shelley, notableWork, Falkner]
-
A.
Falkner
chosen
Falkner is a lesser-known 1837 novel by Mary Shelley that explores themes of guilt, redemption, and complex family relationships.
-
B.
Faulks
Faulks is the surname of British novelist and journalist Sebastian Faulks, best known for his historical and literary fiction.
-
C.
Flecher
Flecher is a variant spelling of the surname Fletcher, which traditionally refers to a maker or seller of arrows.
-
D.
Fowles
Fowles is the surname of Sylvia Fowles, an American professional basketball player renowned as one of the most dominant centers in WNBA history.
-
E.
Flannery
Flannery is the given name of Flannery O'Connor, the influential American writer known for her Southern Gothic short stories and novels.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca838e78748190934d82db3104f855 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc61472cc081909e51b4a35a20ef43 |
completed | April 1, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfaba6f2f481909a30f71e96bc9079 |
completed | April 3, 2026, 11:59 a.m. |
Created at: March 30, 2026, 6:52 p.m.