Triple
T30337980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chess960 |
E771671
|
entity |
| Predicate | skillFocus |
P45342
|
FINISHED |
| Object | reduces advantage of deep opening preparation |
—
|
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: reduces advantage of deep opening preparation | Statement: [Chess960, skillFocus, reduces advantage of deep opening preparation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: skillFocus Context triple: [Chess960, skillFocus, reduces advantage of deep opening preparation]
-
A.
skillEmphasis
chosen
Indicates that a particular skill is given special focus, priority, or importance within a context such as a role, task, or curriculum.
-
B.
skillType
Indicates the specific category or kind of skill that characterizes or classifies an associated skill-related entity or action.
-
C.
skillSet
Indicates that an entity possesses or is associated with a particular collection of skills or competencies.
-
D.
kills
Indicates that one entity causes the death of another entity, ending its life.
-
E.
skillFactor
Indicates the degree or level of skill associated with an entity in performing a particular task or activity.
- 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_69f2248aba24819095bb86480d55b23b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f681ce34048190b4d31e2966949d8c |
completed | May 2, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69f67603526c81908295a1ece8727c66 |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 29, 2026, 7:54 p.m.