Triple
T4145363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port-Royal-des-Champs |
E89368
|
entity |
| Predicate | educationalContribution |
P10669
|
FINISHED |
| Object | innovative pedagogy |
—
|
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: innovative pedagogy | Statement: [Port-Royal-des-Champs, educationalContribution, innovative pedagogy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: educationalContribution Context triple: [Port-Royal-des-Champs, educationalContribution, innovative pedagogy]
-
A.
educationalImpact
chosen
Indicates the effect or influence that one entity has on the learning, knowledge, or educational outcomes of another.
-
B.
educationalImportance
Indicates the degree to which something is significant, valuable, or impactful in an educational or learning context.
-
C.
educates
Indicates that one entity provides instruction, knowledge, or training to another entity.
-
D.
educationalActivity
Indicates an action or relationship in which one entity engages in or provides a learning or teaching activity for another.
-
E.
educationalFocus
Indicates the primary subject area or theme that an educational activity, program, or resource is centered on.
- 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_69aed95785788190ae75bcf0cd1cafdf |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af033ef6648190adde17f943d89c78 |
completed | March 9, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69af018c101081909070da5b11e5eb3d |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:43 p.m.