Triple
T24303517
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sammy’s Hill |
E612465
|
entity |
| Predicate | authorOccupationAtTimeOfWriting |
P938
|
FINISHED |
| Object | television writer |
—
|
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: television writer | Statement: [Sammy’s Hill, authorOccupationAtTimeOfWriting, television writer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: authorOccupationAtTimeOfWriting Context triple: [Sammy’s Hill, authorOccupationAtTimeOfWriting, television writer]
-
A.
authorOccupation
chosen
Indicates the professional role or job that an author holds or is associated with.
-
B.
creatorOccupation
Indicates the professional role or job that the creator of an entity holds or held.
-
C.
hasAuthorOccupationOfAuthor
Indicates that an author has a specific occupation or professional role.
-
D.
authorType
Indicates the specific role or category of authorship associated with an entity, such as primary author, co-author, or editor.
-
E.
publisherProfessionOfAuthor
Indicates that the profession specified is the occupation or professional role of the author associated with a given publisher.
- 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_69e2d7d91bb48190bc5377d17a85fb21 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f292239aa88190847e78ffd31eab4e |
completed | April 29, 2026, 11:20 p.m. |
| PD | Predicate disambiguation | batch_69f1c45c6ec081908401b69424428100 |
completed | April 29, 2026, 8:42 a.m. |
Created at: April 18, 2026, 1:29 a.m.