Triple
T11904642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norman Mailer bibliography |
E283243
|
entity |
| Predicate | focusesOnAuthorProfession |
P938
|
FINISHED |
| Object | novelist |
—
|
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: novelist | Statement: [Norman Mailer bibliography, focusesOnAuthorProfession, novelist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusesOnAuthorProfession Context triple: [Norman Mailer bibliography, focusesOnAuthorProfession, novelist]
-
A.
authorOccupation
chosen
Indicates the professional role or job that an author holds or is associated with.
-
B.
publisherProfessionOfAuthor
Indicates that the profession specified is the occupation or professional role of the author associated with a given publisher.
-
C.
workInAuthorCareer
Indicates that an author’s professional work or role occurs within and is part of their overall writing career.
-
D.
notableWorkFocus
Indicates that a notable work primarily centers on, addresses, or is significantly concerned with a particular subject, theme, or area.
-
E.
authorIsKnownFor
Indicates that a particular author is widely recognized or notable for a specific work, genre, contribution, or characteristic.
- 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_69d6ab2c07e88190ba13b0d21fd6cf33 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8e525460c81909d855048d9c799bf |
completed | April 10, 2026, 11:55 a.m. |
| PD | Predicate disambiguation | batch_69d8bb2fca4481909893f3428b0871ac |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:44 p.m.