Triple
T11727576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blake Farenthold |
E278811
|
entity |
| Predicate | hasEducationDegree |
P6482
|
FINISHED |
| Object | bachelor's degree in radio, television and film |
—
|
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: bachelor's degree in radio, television and film | Statement: [Blake Farenthold, hasEducationDegree, bachelor's degree in radio, television and film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEducationDegree Context triple: [Blake Farenthold, hasEducationDegree, bachelor's degree in radio, television and film]
-
A.
hasDegree
chosen
Indicates that an entity possesses or has been awarded a specific academic or professional degree.
-
B.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
-
C.
educatedAt
Indicates that an entity received education or formal training at a specified institution or place of learning.
-
D.
eligibleDegree
Indicates that an academic degree qualifies its holder to be considered eligible for a particular program, position, or requirement.
-
E.
hasHigherEducationAccess
Indicates that one entity has access to higher education opportunities or institutions relative to another entity or context.
- 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_69d6aaffec6881908bead509e8621742 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4d70d908190b5f47c2ef501a191 |
completed | April 10, 2026, 7:20 a.m. |
| PD | Predicate disambiguation | batch_69d88a7f51248190bf492bd7509b5413 |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:41 p.m.