Triple
T26904514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Design Innovation |
E677216
|
entity |
| Predicate | developsSkillsIn |
P98489
|
FINISHED |
| Object | creative problem solving |
—
|
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: creative problem solving | Statement: [Design Innovation, developsSkillsIn, creative problem solving]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: developsSkillsIn Context triple: [Design Innovation, developsSkillsIn, creative problem solving]
-
A.
developsSkill
chosen
Indicates that one entity causes or contributes to the growth, improvement, or acquisition of a particular skill in another entity.
-
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.
learnsSkill
Indicates that an entity acquires or develops a particular skill through learning or practice.
-
E.
indicatesSkill
Indicates a relationship where one entity possesses, demonstrates, or is associated with a particular skill represented by another entity.
- 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_69eee9bcef1c8190be88586bb902bb9b |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f67257b0448190a13011af81c81449 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 27, 2026, 5:58 a.m.