Triple
T495122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GRE |
E10274
|
entity |
| Predicate | measuresSkill |
P750
|
FINISHED |
| Object | academic readiness for graduate-level work |
—
|
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: academic readiness for graduate-level work | Statement: [GRE, measuresSkill, academic readiness for graduate-level work]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: measuresSkill Context triple: [GRE, measuresSkill, academic readiness for graduate-level work]
-
A.
requiresSkill
Indicates that performing or engaging in one entity (e.g., a task or role) depends on possessing or applying a specific skill represented by the other entity.
-
B.
hasCompetence
Indicates that an entity possesses the ability, skill, or qualification to perform a specific task or function effectively.
-
C.
hasMeasurementDifficulty
Indicates that performing a measurement on something is challenging or problematic in some way.
-
D.
hasTechnique
Indicates that an entity employs, utilizes, or is associated with a particular method, procedure, or technique.
-
E.
assessmentMethod
chosen
Indicates the method or procedure used to evaluate, measure, or judge something.
- 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_69a2e847df8481909239ec08ccf1e376 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f0fdd5608190815fa36485df8962 |
completed | Feb. 28, 2026, 1:43 p.m. |
| PD | Predicate disambiguation | batch_69a2edf90ca88190b6a182e5b6733612 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.