Triple
T18301922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IFLA Library Reference Model |
E438376
|
entity |
| Predicate | definesRelationshipType |
P105807
|
FINISHED |
| Object | is created by |
—
|
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: is created by | Statement: [IFLA Library Reference Model, definesRelationshipType, is created by]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: definesRelationshipType Context triple: [IFLA Library Reference Model, definesRelationshipType, is created by]
-
A.
definesRelationshipBetween
Indicates that one entity specifies or establishes the nature, type, or rules of a relationship that exists between two or more other entities.
-
B.
definesRelationshipAs
chosen
Indicates that one entity explicitly specifies or establishes the type or nature of the relationship that holds between two or more entities.
-
C.
definesType
Indicates that one entity specifies or establishes the type or classification of another entity.
-
D.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
-
E.
definitionType
Indicates the specific kind or category of definition that characterizes how one entity is defined in relation to another.
- 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_69d8b915e3e881909125d760c15d0c29 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50180ac48819090e9a8f11ba10c3d |
completed | April 19, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69e44fdf43d08190bbcfb6b1fe3cc0ee |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:35 a.m.