Triple
T12230465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Master of Policy Management |
E291461
|
entity |
| Predicate | skillTaught |
P103919
|
FINISHED |
| Object | policy analysis |
—
|
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: policy analysis | Statement: [Master of Policy Management, skillTaught, policy analysis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: skillTaught Context triple: [Master of Policy Management, skillTaught, policy analysis]
-
A.
skillAssessed
Indicates that an entity’s skill or competency has been evaluated or measured, typically by another agent or process.
-
B.
skillSet
Indicates that an entity possesses or is associated with a particular collection of skills or competencies.
-
C.
skilledIn
Indicates that an entity possesses ability, expertise, or proficiency in performing or using another entity (such as a task, tool, or domain).
-
D.
indicatesSkill
Indicates a relationship where one entity possesses, demonstrates, or is associated with a particular skill represented by another entity.
-
E.
kills
Indicates that one entity causes the death of another entity, ending its life.
- 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_69d6ab668acc8190963ba424049d6aee |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d924a3973c8190a882046963b320fb |
completed | April 10, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69d91c41bcbc81909782f4e3c571b218 |
completed | April 10, 2026, 3:50 p.m. |
| PDg | Predicate description generation | batch_69d92468052c819090546f36d009a64f |
completed | April 10, 2026, 4:25 p.m. |
Created at: April 8, 2026, 9:51 p.m.