Triple
T25034896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colossus: The Rise and Fall of the American Empire |
E626948
|
entity |
| Predicate | nonFictionSubjectCategory |
P17629
|
FINISHED |
| Object | geopolitics |
—
|
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: geopolitics | Statement: [Colossus: The Rise and Fall of the American Empire, nonFictionSubjectCategory, geopolitics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nonFictionSubjectCategory Context triple: [Colossus: The Rise and Fall of the American Empire, nonFictionSubjectCategory, geopolitics]
-
A.
isNonFictionCategory
chosen
Indicates that a given category pertains to non-fiction works, such as factual or informational content rather than fictional material.
-
B.
isNonfiction
Indicates that the work or content is factual rather than fictional, based on real events, people, or information.
-
C.
bookCategory
Indicates the classification or genre category to which a given book belongs.
-
D.
subjectCategories
Indicates that an entity is associated with one or more subject-based categories or classifications.
-
E.
coreCategory
Indicates that one entity is the primary or fundamental category to which another entity belongs or is classified under.
- 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_69e2ff2a2c088190be513727ee8bfe78 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f464b4c9b0819085daa00c7c3b8b76 |
completed | May 1, 2026, 8:30 a.m. |
| PD | Predicate disambiguation | batch_69f45cfb53f4819099bba48c5057e787 |
completed | May 1, 2026, 7:57 a.m. |
Created at: April 18, 2026, 6:08 a.m.