Triple
T28513031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NMC Horizon Project |
E721541
|
entity |
| Predicate | analyzesImpactOn |
P50422
|
FINISHED |
| Object | teaching practices |
—
|
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: teaching practices | Statement: [NMC Horizon Project, analyzesImpactOn, teaching practices]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: analyzesImpactOn Context triple: [NMC Horizon Project, analyzesImpactOn, teaching practices]
-
A.
examinesImpactOn
chosen
Indicates that one entity studies, evaluates, or analyzes the effects or consequences that another entity has on a specified subject or outcome.
-
B.
recognizesImpactOn
Indicates that one entity acknowledges or understands the effect or consequences it has on another entity or situation.
-
C.
exportImpact
Indicates the effect or consequences that an entity’s exports have on another entity, system, or context.
-
D.
measuresImpactIn
Indicates that an action or entity evaluates or quantifies its effect or influence within a specified context, domain, or environment.
-
E.
hasImpactScale
Indicates the degree or magnitude of impact that one entity or action has on another, typically expressed along a defined scale.
- 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_69f01a5c072081908c7b04bcf6478da9 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f652a492108190b885b955ce147d3c |
completed | May 2, 2026, 7:38 p.m. |
| PD | Predicate disambiguation | batch_69f651aad92c8190b874b3b5f9f64434 |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 28, 2026, 3:14 a.m.