Triple
T29841904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FI TURKU02 |
E757821
|
entity |
| Predicate | associatedWithEntityType |
P207179
|
FINISHED |
| Object | university |
—
|
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: university | Statement: [FI TURKU02, associatedWithEntityType, university]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithEntityType Context triple: [FI TURKU02, associatedWithEntityType, university]
-
A.
associatedWithRelationship
Indicates a general connection or involvement between entities through some form of relationship, without specifying its exact nature.
-
B.
associatedWithAssociation
Indicates a relationship where an entity is linked or connected to a particular association or organization.
-
C.
associatedWithAttribute
Indicates that one entity is linked to, characterized by, or described through a particular attribute.
-
D.
includedEntityType
Indicates that one entity type is contained within, or forms a component part of, another entity type.
-
E.
associatedWithModel
Indicates that one entity has a defined connection, linkage, or relationship with a particular model.
- 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_69f224593f6c81908785a560fe659f58 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e0f3d88190a4ee7b0673f1ef90 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7ee0388190a29faeb5cdb0950a |
completed | May 12, 2026, 7:16 p.m. |
Created at: April 29, 2026, 5:39 p.m.