Triple
T11036851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agatha Christie's Marple |
E260906
|
entity |
| Predicate | hasStorySource |
P44758
|
FINISHED |
| Object | Agatha Christie novels |
—
|
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: Agatha Christie novels | Statement: [Agatha Christie's Marple, hasStorySource, Agatha Christie novels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStorySource Context triple: [Agatha Christie's Marple, hasStorySource, Agatha Christie novels]
-
A.
sourceOfStories
chosen
Indicates that one entity serves as the origin or provider of stories for another entity.
-
B.
originStoryIncludes
Indicates that an entity’s origin story contains, involves, or features the referenced element as a component or part of that backstory.
-
C.
hasStoryPath
Indicates that there exists a defined narrative route or sequence of events connecting one entity to another within a story or interactive experience.
-
D.
hasSourceWork
Indicates that something originates from, is derived from, or is based on a particular source work.
-
E.
storyBy
Indicates that one entity is the creator or author of the story associated with another entity.
- 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_69d6aa979bdc8190bf0e79104cc098c1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797e9e3fc8190802195ac9fcb8e28 |
completed | April 9, 2026, 12:13 p.m. |
| PD | Predicate disambiguation | batch_69d74407cb088190ba37c8da3d342b64 |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:25 p.m.