Triple
T26212276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OWL 2 Manchester syntax |
E655519
|
entity |
| Predicate | hasExampleKeyword |
P168052
|
FINISHED |
| Object | and |
—
|
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: and | Statement: [OWL 2 Manchester syntax, hasExampleKeyword, and]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasExampleKeyword Context triple: [OWL 2 Manchester syntax, hasExampleKeyword, and]
-
A.
hasExample
Indicates that one entity serves as an instance, illustration, or concrete example of another entity.
-
B.
hasExampleType
Indicates that something is associated with a specific type or category of example that characterizes or illustrates it.
-
C.
hasExampleProvider
Indicates that one entity serves as an example provider or source of illustrative instances for another entity.
-
D.
hasExampleImplementation
Indicates that an entity is accompanied by a concrete implementation that serves as an example of how it can be realized or used.
-
E.
hasNonExample
Indicates that something is associated with an instance that explicitly does not satisfy or illustrate a given concept, rule, or category.
- F. None of above. chosen
Provenance (4 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_69ee5b49adb4819086545280d4ef6337 |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f673633d288190b52ceb9f8a057c44 |
completed | May 2, 2026, 9:57 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
| PDg | Predicate description generation | batch_69f67256d064819094be04fc1bbbc635 |
completed | May 2, 2026, 9:53 p.m. |
Created at: April 26, 2026, 8:52 p.m.