Triple
T4861436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Simon Jordan |
E108667
|
entity |
| Predicate | linkedToRealEvents |
P33853
|
FINISHED |
| Object | inspired by the historical Grace Marks case |
—
|
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: inspired by the historical Grace Marks case | Statement: [Dr. Simon Jordan, linkedToRealEvents, inspired by the historical Grace Marks case]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linkedToRealEvents Context triple: [Dr. Simon Jordan, linkedToRealEvents, inspired by the historical Grace Marks case]
-
A.
usesRealHistoricalEvents
Indicates that the subject incorporates or is based on actual events that occurred in real history.
-
B.
basedOnEventsDescribedIn
chosen
Indicates that something is derived from, inspired by, or constructed using the events described in another source.
-
C.
historicallyLinked
Indicates that two entities are connected through a shared or related historical event, period, or development.
-
D.
inspiredEvent
Indicates that one event served as the motivation, cause, or creative stimulus for another event to occur or be conceived.
-
E.
hasHistoricalEvent
Indicates that a historical event occurred in, is associated with, or is relevant to a particular 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_69bd440b965081908b0557721cae6338 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6d5f62b48190b367ed1b850cfbcb |
completed | March 20, 2026, 3:53 p.m. |
| PD | Predicate disambiguation | batch_69bd6c27334481909ba8ac80854f7d8e |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:26 p.m.