Triple
T28707497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sex and the Single Girl |
E729732
|
entity |
| Predicate | nonFictionSourceGenre |
P37108
|
FINISHED |
| Object | self-help |
—
|
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: self-help | Statement: [Sex and the Single Girl, nonFictionSourceGenre, self-help]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nonFictionSourceGenre Context triple: [Sex and the Single Girl, nonFictionSourceGenre, self-help]
-
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.
genreDocumented
Indicates that a work’s genre has been formally recorded or documented.
-
D.
literaryGenreOfSourceWork
Indicates that a work belongs to, or is characterized by, a particular literary genre.
-
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_69f043e7d5a4819094b18aca10b1e024 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f656d4e7b081909ba541afc649a059 |
completed | May 2, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69f651ac855481908e30c3b345d31356 |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 28, 2026, 5:46 a.m.