Triple
T4208905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Prairie |
E93849
|
entity |
| Predicate | timeOfAuthorCareer |
P30618
|
FINISHED |
| Object | early career of James Fenimore Cooper |
—
|
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: early career of James Fenimore Cooper | Statement: [The Prairie, timeOfAuthorCareer, early career of James Fenimore Cooper]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeOfAuthorCareer Context triple: [The Prairie, timeOfAuthorCareer, early career of James Fenimore Cooper]
-
A.
authorLifespanContext
Indicates the temporal or historical context of an author’s life span in relation to other events, periods, or entities.
-
B.
timeInArtistCareer
chosen
Indicates the point or period within an artist’s professional career at which a given event, work, or activity occurs.
-
C.
activeYearsInCareer
Indicates the span of time during which an entity was actively engaged in a particular career or professional field.
-
D.
activeYearsInLiterature
Indicates the span of years during which an entity was actively producing or contributing to literary works.
-
E.
creatorLifespan
Indicates the time period between the birth and death of the creator associated with an 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_69b3451743608190808f41d17ccf2650 |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b34e098da881909a0cc339cc186627 |
completed | March 12, 2026, 11:36 p.m. |
| PD | Predicate disambiguation | batch_69b347efd9b08190bb50f82e4e7fe06d |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:03 p.m.