Triple
T33464908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abel Magwitch |
E857018
|
entity |
| Predicate | hasBackstoryWith |
P187067
|
FINISHED |
| Object | Miss Havisham |
—
|
NE NERFINISHED |
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: Miss Havisham | Statement: [Abel Magwitch, hasBackstoryWith, Miss Havisham]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBackstoryWith Context triple: [Abel Magwitch, hasBackstoryWith, Miss Havisham]
-
A.
hasFictionalBackstory
Indicates that an entity is associated with an invented or imaginary narrative background rather than a real-world history.
-
B.
hasKeyFigureInBackstory
chosen
Indicates that an entity’s background narrative prominently features a particular individual who significantly influences or shapes that backstory.
-
C.
expandsBackstoryOf
Indicates that one entity provides additional background details or context that elaborate on the history or origins of another entity.
-
D.
settingOfCharacterBackstory
Indicates the place or environment in which a character’s backstory events occur.
-
E.
allegedBackstory
Indicates that a claimed or reported background story is associated with an entity, without asserting its truth.
- 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_69f34973461481909c701c98ebd75623 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fd0b92f42881908cd77e3f058adcc2 |
completed | May 7, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fd0a3d68d4819094d92040f7c48d7c |
completed | May 7, 2026, 9:55 p.m. |
Created at: May 1, 2026, 1:37 a.m.