Triple
T30763191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Lamentation of Doctor Faustus |
E783290
|
entity |
| Predicate | workRoleInNovel |
P11527
|
FINISHED |
| Object | central artistic achievement of Adrian Leverkühn |
—
|
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: central artistic achievement of Adrian Leverkühn | Statement: [The Lamentation of Doctor Faustus, workRoleInNovel, central artistic achievement of Adrian Leverkühn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workRoleInNovel Context triple: [The Lamentation of Doctor Faustus, workRoleInNovel, central artistic achievement of Adrian Leverkühn]
-
A.
literaryRole
Indicates the specific narrative or functional role an entity holds within a literary work or text.
-
B.
characterInWorkDescribedAs
Indicates that a character is portrayed or described in a particular way within a specific work.
-
C.
workTitleOfCharacter
Indicates that the specified work (e.g., book, film, game) is the title in which the given character appears.
-
D.
otherProtagonistOccupation
Indicates that another main character in the narrative has a specific occupation or job role.
-
E.
roleInText
chosen
Indicates that an entity participates in a text with a specific function or capacity (e.g., author, editor, character).
- 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_69f224b047f48190b4f5efeb7ee97b37 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f68fba02708190a1d0392453790fd8 |
completed | May 2, 2026, 11:58 p.m. |
| PD | Predicate disambiguation | batch_69f686140aa08190a35f62572b2db9b6 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 29, 2026, 8:39 p.m.