Triple
T8731969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Corey |
E207276
|
entity |
| Predicate | hasEducationBackground |
P45956
|
FINISHED |
| Object | well educated |
—
|
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: well educated | Statement: [Tom Corey, hasEducationBackground, well educated]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEducationBackground Context triple: [Tom Corey, hasEducationBackground, well educated]
-
A.
hasAcademicBackgroundIn
Indicates that an entity possesses formal education, training, or scholarly experience in a specified academic field or discipline.
-
B.
hasEducationalProfile
chosen
Indicates that an entity is associated with a specific educational profile, detailing its education-related characteristics, qualifications, or academic background.
-
C.
educatedAt
Indicates that an entity received education or formal training at a specified institution or place of learning.
-
D.
hasEducationSetNumber
Indicates that an entity is associated with a specific numbered set or grouping of educational records or qualifications.
-
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_69ca8358e4008190898471a59b96c301 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d27efb88190b42d5bc9774d9c63 |
completed | March 31, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69cc457093188190959287a6458651c6 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:37 p.m.