Triple
T3944809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Michael Bluth |
E92119
|
entity |
| Predicate | laterEducation |
P27439
|
FINISHED |
| Object | college student |
—
|
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: college student | Statement: [George Michael Bluth, laterEducation, college student]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterEducation Context triple: [George Michael Bluth, laterEducation, college student]
-
A.
educationRight
Indicates that an entity holds a right or entitlement to receive education or educational opportunities.
-
B.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
C.
educates
Indicates that one entity provides instruction, knowledge, or training to another entity.
-
D.
educatedAt
Indicates that an entity received education or formal training at a specified institution or place of learning.
-
E.
educationStatus
chosen
Indicates the current or achieved level, stage, or condition of an entity’s formal education.
- 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_69aed965502c8190904ebad1203a4ae8 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee764235081909309b3c982f322a9 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:24 p.m.