Triple
T1795571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Why Is Sex Fun? |
E39594
|
entity |
| Predicate | coverSubject |
P7040
|
FINISHED |
| Object | human mating and reproduction |
—
|
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: human mating and reproduction | Statement: [Why Is Sex Fun?, coverSubject, human mating and reproduction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coverSubject Context triple: [Why Is Sex Fun?, coverSubject, human mating and reproduction]
-
A.
subjectMatter
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
-
B.
subjectType
Indicates the classification or category that defines what kind of entity the subject is.
-
C.
coverUpBy
Indicates that one entity conceals, suppresses, or hides the actions, information, or wrongdoing associated with another entity.
-
D.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
E.
subjectOfWork
chosen
Indicates that one entity is the main topic, focus, or theme that a particular work (such as a book, article, or artwork) is about.
- 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_69a88631854081909723959921e45c2b |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab61b6ea188190aab9fb839bf1e367 |
completed | March 6, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69aa61d2f7a8819090301f92d3e358c7 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:32 p.m.