Triple
T17038108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | mixed short track speed skating relay |
E413372
|
entity |
| Predicate | hasKeySkill |
P6204
|
FINISHED |
| Object | cornering technique |
—
|
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: cornering technique | Statement: [mixed short track speed skating relay, hasKeySkill, cornering technique]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasKeySkill Context triple: [mixed short track speed skating relay, hasKeySkill, cornering technique]
-
A.
hasSkillTree
Indicates that an entity is associated with a structured progression of skills or abilities, typically organized in a branching or hierarchical form.
-
B.
hasEponymousSkill
Indicates that an entity possesses a skill that is named after a particular person or entity.
-
C.
indicatesSkill
Indicates a relationship where one entity possesses, demonstrates, or is associated with a particular skill represented by another entity.
-
D.
requiresSkill
chosen
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.
-
E.
hasCompetence
Indicates that an entity possesses the ability, skill, or qualification to perform a specific task or function effectively.
- 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_69d886cd18288190b006abab23f811b7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d8f45f84819092cfb27cc33da026 |
completed | April 18, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69e35d60a588819084f53ef9f8b2e7c0 |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:33 a.m.