Triple
T6552579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Institutiones |
E151163
|
entity |
| Predicate | influenceOnEducation |
P10669
|
FINISHED |
| Object | standard text in medieval law schools |
—
|
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: standard text in medieval law schools | Statement: [Institutiones, influenceOnEducation, standard text in medieval law schools]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influenceOnEducation Context triple: [Institutiones, influenceOnEducation, standard text in medieval law schools]
-
A.
educationalImpact
chosen
Indicates the effect or influence that one entity has on the learning, knowledge, or educational outcomes of another.
-
B.
educationRight
Indicates that an entity holds a right or entitlement to receive education or educational opportunities.
-
C.
educationalImportance
Indicates the degree to which something is significant, valuable, or impactful in an educational or learning context.
-
D.
educationPolicy
Indicates a relationship where an authority or entity establishes, governs, or influences rules, strategies, or frameworks guiding an education system or educational practices.
-
E.
educates
Indicates that one entity provides instruction, knowledge, or training to another entity.
- 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_69c687f3fd60819083bfa583e5bcfa71 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c1b15d3481908ae66e3d7564b352 |
completed | March 27, 2026, 5:43 p.m. |
| PD | Predicate disambiguation | batch_69c6acf6d4148190914b19e9affd8c76 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:51 p.m.