Triple
T26832488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sexual Behavior in the Human Female |
E675536
|
entity |
| Predicate | nonFictionGenre |
P37108
|
FINISHED |
| Object | scientific literature |
—
|
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: scientific literature | Statement: [Sexual Behavior in the Human Female, nonFictionGenre, scientific literature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nonFictionGenre Context triple: [Sexual Behavior in the Human Female, nonFictionGenre, scientific literature]
-
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.
hasWrittenNonFiction
Indicates that a person is the author of one or more non-fiction works.
-
D.
fictionalGenre
Indicates that a work of fiction belongs to or is categorized under a particular narrative genre or style.
-
E.
bookCategory
chosen
Indicates the classification or genre category to which a given book belongs.
- 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_69eee9b776448190993a60b67fcc9545 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f61ade18808190954f582501af4842 |
completed | May 2, 2026, 3:40 p.m. |
| PD | Predicate disambiguation | batch_69f611ad2eb48190ac1ed0090f13f7a9 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 5:02 a.m.