Triple
T33210100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Judge Hatlee Beech |
E850130
|
entity |
| Predicate | workAuthorSpecialization |
P110441
|
FINISHED |
| Object | legal thrillers |
—
|
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: legal thrillers | Statement: [Judge Hatlee Beech, workAuthorSpecialization, legal thrillers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workAuthorSpecialization Context triple: [Judge Hatlee Beech, workAuthorSpecialization, legal thrillers]
-
A.
authorOccupation
Indicates the professional role or job that an author holds or is associated with.
-
B.
hasAuthorOccupationOfAuthor
Indicates that an author has a specific occupation or professional role.
-
C.
coAuthorOccupation
Indicates that two or more co-authors share the same or closely related professional occupation.
-
D.
genreOfWorkHeWrites
chosen
Indicates that a person is an author who writes works belonging to a particular genre.
-
E.
academicFieldOfAuthor
Indicates the academic discipline or field in which an author conducts their scholarly work or produces publications.
- 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_69f3495fb92c819083ce65d0ddee7a76 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6e02ba6b881908dfafc52d3b75f1c |
completed | May 3, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_69f6de09c2f481909f8b2545d3208c9f |
completed | May 3, 2026, 5:32 a.m. |
Created at: May 1, 2026, 1:30 a.m.