Triple
T21943555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ben Fountain |
E541879
|
entity |
| Predicate | professionBeforeWriting |
P938
|
FINISHED |
| Object | lawyer |
—
|
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: lawyer | Statement: [Ben Fountain, professionBeforeWriting, lawyer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionBeforeWriting Context triple: [Ben Fountain, professionBeforeWriting, lawyer]
-
A.
professionBeforePolitics
Indicates that a person’s occupation or career occurred prior to their involvement in politics.
-
B.
leftProfession
Indicates that an entity has stopped or abandoned a particular profession or occupation they previously held.
-
C.
hasGivenProfession
Indicates that an entity holds or practices a specified profession or occupation.
-
D.
authorOccupation
chosen
Indicates the professional role or job that an author holds or is associated with.
-
E.
professionalCategory
Indicates the classification of an entity according to its professional field, role, or occupational domain.
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1242515ec8190b015bf8c7b13be85 |
completed | April 28, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69e6f5efc208819091ed2cf6841fa600 |
completed | April 21, 2026, 3:58 a.m. |
Created at: April 16, 2026, 7:56 p.m.