Triple
T16841529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Felpersham |
E409423
|
entity |
| Predicate | usedForPlotType |
P101982
|
FINISHED |
| Object | legal storylines |
—
|
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: legal storylines | Statement: [Felpersham, usedForPlotType, legal storylines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedForPlotType Context triple: [Felpersham, usedForPlotType, legal storylines]
-
A.
commonPlotUse
chosen
Indicates that a particular plot element, device, or storyline is frequently employed or reused across multiple works or narratives.
-
B.
usedInType
Indicates that something serves as a component, element, or example within a particular type or category.
-
C.
usesGraphType
Indicates that one entity employs or is configured to operate with a specific type of graph representation or graph model.
-
D.
hasPlot
Indicates that an entity (such as a narrative work) possesses or is associated with a specific storyline or sequence of events.
-
E.
usedFor
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
- 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_69d883952b048190887740a980b712ed |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b35167a48190b45a459023e3ab1b |
completed | April 18, 2026, 4:37 p.m. |
| PD | Predicate disambiguation | batch_69e32b87b4248190aaddb05e88452356 |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:24 a.m.