Triple
T8770017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Turku |
E208432
|
entity |
| Predicate | hasStrongField |
P85295
|
FINISHED |
| Object | biomedical sciences |
—
|
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: biomedical sciences | Statement: [University of Turku, hasStrongField, biomedical sciences]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStrongField Context triple: [University of Turku, hasStrongField, biomedical sciences]
-
A.
hasFieldFormation
Indicates that an entity possesses or exhibits a particular field formation, such as a structured arrangement or configuration of fields.
-
B.
hasFieldName
Indicates that one entity is associated with, or identified by, a specific field name in a data structure or schema.
-
C.
hasInfield
Indicates that an entity possesses or includes a designated infield area, typically within a larger spatial or structural context.
-
D.
hasStrongCurrent
Indicates that one entity (typically a body of water or medium) possesses a powerful, fast-moving flow or current relative to a reference point or standard.
-
E.
hasForceStrength
Indicates that one entity possesses a certain level or degree of physical or exerted force strength in relation to another entity or context.
- 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_69ca835edb4481909b4aafb616dc5eb7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5eedc7188190a67d959b9af53837 |
completed | March 31, 2026, 11:55 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1aff3881908be6a9cbc9f50461 |
completed | March 31, 2026, 11:43 p.m. |
| PDg | Predicate description generation | batch_69cc5cfddef48190aee764ee7b25bae9 |
completed | March 31, 2026, 11:47 p.m. |
Created at: March 30, 2026, 6:41 p.m.