Triple
T29165262
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Human Document |
E739299
|
entity |
| Predicate | hasNonFictionContent |
P24758
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [A Human Document, hasNonFictionContent, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNonFictionContent Context triple: [A Human Document, hasNonFictionContent, true]
-
A.
isNonFictionEligible
Indicates that an item meets the criteria to be classified or treated as eligible non-fiction.
-
B.
isNonfiction
chosen
Indicates that the work or content is factual rather than fictional, based on real events, people, or information.
-
C.
hasWrittenNonFiction
Indicates that a person is the author of one or more non-fiction works.
-
D.
hasFictionComponent
Indicates that something includes, contains, or is composed in part of a fictional element or work.
-
E.
isNonFictionCategory
Indicates that a given category pertains to non-fiction works, such as factual or informational content rather than fictional material.
- 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_69f07cb528fc8190a556b73990c347c8 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69ff80d9a1d88190a95b1488acd6e2e5 |
completed | May 9, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69ff802ae2dc819093a3cda42b63dcbd |
completed | May 9, 2026, 6:42 p.m. |
Created at: April 28, 2026, 11:49 a.m.