Triple
T27409120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deanna Dwyer |
E692091
|
entity |
| Predicate | realNameNotableFor |
P112540
|
FINISHED |
| Object | bestselling suspense and horror novels |
—
|
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: bestselling suspense and horror novels | Statement: [Deanna Dwyer, realNameNotableFor, bestselling suspense and horror novels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: realNameNotableFor Context triple: [Deanna Dwyer, realNameNotableFor, bestselling suspense and horror novels]
-
A.
namedPersonNotableFor
chosen
Indicates that a person is especially known or recognized for a particular work, role, achievement, or characteristic.
-
B.
namedForNotablePersonFrom
Indicates that one entity is named in honor of a notable person who originates from another specified place or group.
-
C.
notablePublicFigure
Indicates that the subject is widely recognized and holds a significant public profile or influence in society.
-
D.
notableHuman
Indicates that the subject is a human who is recognized as notable or significant in some context.
-
E.
notableStarName
Indicates that the subject is known by the specified star name as a notable or prominent designation.
- 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_69ef5205fc808190ad3efc5525b8e6d6 |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f62cd99324819099a95e2729e966e9 |
completed | May 2, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69f62c1762f881908c25e8f70ecd5041 |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 12:31 p.m.