Triple
T15400133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Homesick: A Memoir |
E368290
|
entity |
| Predicate | featuresOccupationOfAuthor |
P938
|
FINISHED |
| Object | actress |
—
|
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: actress | Statement: [Homesick: A Memoir, featuresOccupationOfAuthor, actress]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresOccupationOfAuthor Context triple: [Homesick: A Memoir, featuresOccupationOfAuthor, actress]
-
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.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
D.
workInAuthorCareer
Indicates that an author’s professional work or role occurs within and is part of their overall writing career.
-
E.
genreOfWorkHeWrites
Indicates that a person is an author who writes works belonging to a particular genre.
- 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e8d89e08190b7cae778d89fb5e1 |
completed | April 16, 2026, 1:42 a.m. |
| PD | Predicate disambiguation | batch_69ded27b8cac8190bfa77698d53c5d1c |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:19 a.m.