Triple
T30223068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liberal Arts |
E768401
|
entity |
| Predicate | hasEducationTheme |
P173745
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Liberal Arts, hasEducationTheme, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEducationTheme Context triple: [Liberal Arts, hasEducationTheme, true]
-
A.
hasEducationalScope
Indicates that an entity is associated with a particular educational level, range, or context that defines the scope of its relevance or applicability.
-
B.
hasEducationalDimension
Indicates that something includes, involves, or contributes to an educational aspect, purpose, or impact within the relationship or context described.
-
C.
hasEducationIn
Indicates that an entity has received education, training, or formal study in a specified field, subject, or discipline.
-
D.
hasEducationCharacteristic
Indicates that an entity possesses a specific educational attribute, quality, or feature (such as level, type, or status of education).
-
E.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
- F. None of above. chosen
Provenance (4 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_69f2247fd8b8819087fcf83cb7a05eb8 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6b9a84ff88190ab5a71f7ef1e0dac |
completed | May 3, 2026, 2:57 a.m. |
| PD | Predicate disambiguation | batch_69f6b626120c819097c9ad04487570d7 |
completed | May 3, 2026, 2:42 a.m. |
| PDg | Predicate description generation | batch_69f6b8fe147881908ba17483c7b13f05 |
completed | May 3, 2026, 2:54 a.m. |
Created at: April 29, 2026, 7:35 p.m.