Triple
T12110559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Collins COBUILD Advanced Learner’s Dictionary |
E288416
|
entity |
| Predicate | hasExampleType |
P103345
|
FINISHED |
| Object | corpus-attested examples |
—
|
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: corpus-attested examples | Statement: [Collins COBUILD Advanced Learner’s Dictionary, hasExampleType, corpus-attested examples]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasExampleType Context triple: [Collins COBUILD Advanced Learner’s Dictionary, hasExampleType, corpus-attested examples]
-
A.
hasExample
Indicates that one entity serves as an instance, illustration, or concrete example of another entity.
-
B.
hasNonExample
Indicates that something is associated with an instance that explicitly does not satisfy or illustrate a given concept, rule, or category.
-
C.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
-
D.
hasElementType
Indicates that something is composed of or contains elements that are of a specified type.
-
E.
hasNumberOfTypes
Indicates that an entity is associated with a specific count of distinct types or categories it possesses or includes.
- 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_69d6ab4a5c448190a110d1273314b21a |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9164ada5081908676bd9e5947268a |
completed | April 10, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69d9150497408190921334d21503375a |
completed | April 10, 2026, 3:19 p.m. |
| PDg | Predicate description generation | batch_69d916481a008190ae66677b9e6dd961 |
completed | April 10, 2026, 3:24 p.m. |
Created at: April 8, 2026, 9:49 p.m.