Triple
T25602127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OWL 2 functional-style syntax |
E641813
|
entity |
| Predicate | hasKeywordStyle |
P1609
|
FINISHED |
| Object | capitalized construct names |
—
|
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: capitalized construct names | Statement: [OWL 2 functional-style syntax, hasKeywordStyle, capitalized construct names]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasKeywordStyle Context triple: [OWL 2 functional-style syntax, hasKeywordStyle, capitalized construct names]
-
A.
hasStyle
chosen
Indicates that an entity possesses, exhibits, or is characterized by a particular style or manner.
-
B.
hasRuleStyle
Indicates that an entity is associated with a particular rule-based style or formatting specification.
-
C.
hasPowerStyle
Indicates that one entity possesses or exhibits a particular style or manner of using power in relation to another entity or context.
-
D.
hasSubstyle
Indicates that one style is a more specific or subordinate variant of another style within a hierarchical style structure.
-
E.
hasStructuralStyle
Indicates that one entity possesses, exhibits, or is characterized by a particular architectural or structural design style.
- 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_69e75dc60d108190b7e2419e36b0134b |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f65aa07c048190a5df30d53d8f0cf5 |
completed | May 2, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f659cc571c819097e51e531961d812 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 21, 2026, 4:31 p.m.