Triple
T11935778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TVA: Democracy on the March |
E284038
|
entity |
| Predicate | nonFictionSubjectArea |
P96519
|
FINISHED |
| Object | political science |
—
|
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: political science | Statement: [TVA: Democracy on the March, nonFictionSubjectArea, political science]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nonFictionSubjectArea Context triple: [TVA: Democracy on the March, nonFictionSubjectArea, political science]
-
A.
isNonfiction
Indicates that the work or content is factual rather than fictional, based on real events, people, or information.
-
B.
isNonFictionCategory
Indicates that a given category pertains to non-fiction works, such as factual or informational content rather than fictional material.
-
C.
primarySubjectArea
chosen
Indicates the main academic or topical field to which something (such as a work, course, or resource) is most centrally related.
-
D.
hasWrittenNonFiction
Indicates that a person is the author of one or more non-fiction works.
-
E.
nonScholastic
Indicates that an activity, event, or attribute is related to areas outside formal academic or scholarly pursuits.
- 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_69d6ab2ce9c48190b5d39511b524f666 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90306fcf48190a963d2d1932288d1 |
completed | April 10, 2026, 2:02 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3af0188190bfb22be5c97b3349 |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:45 p.m.