Triple
T8940444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LLM in European Private Law |
E212885
|
entity |
| Predicate | targetSkills |
P58200
|
FINISHED |
| Object | comparative legal 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: comparative legal analysis | Statement: [LLM in European Private Law, targetSkills, comparative legal analysis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetSkills Context triple: [LLM in European Private Law, targetSkills, comparative legal analysis]
-
A.
skillSet
chosen
Indicates that an entity possesses or is associated with a particular collection of skills or competencies.
-
B.
skillEmphasis
Indicates that a particular skill is given special focus, priority, or importance within a context such as a role, task, or curriculum.
-
C.
notableRecruitingSkill
Indicates that an entity is recognized for having significant or distinguished ability in recruiting others.
-
D.
skillAssessed
Indicates that an entity’s skill or competency has been evaluated or measured, typically by another agent or process.
-
E.
kills
Indicates that one entity causes the death of another entity, ending its life.
- 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_69ca839694c88190b324ffeb43d23b08 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc66b8b37c8190bce6e049de8cf732 |
completed | April 1, 2026, 12:28 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed5267c8190a43feb2a2f3df1ec |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 6:58 p.m.