Triple
T36867728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laura |
E911130
|
entity |
| Predicate | hasAlternativeNameInScholarship |
P196479
|
FINISHED |
| Object | Laura of Styria |
—
|
NE NERFINISHED |
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: Laura of Styria | Statement: [Laura, hasAlternativeNameInScholarship, Laura of Styria]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlternativeNameInScholarship Context triple: [Laura, hasAlternativeNameInScholarship, Laura of Styria]
-
A.
hasTitleInScholarship
Indicates that an entity holds or is associated with a specific title within an academic or scholarly context.
-
B.
scholarshipEquivalency
Indicates that one scholarship is considered equal in value, coverage, or benefit to another scholarship or financial award.
-
C.
scholarshipType
Indicates the specific category or kind of scholarship associated with an entity.
-
D.
hasScholarshipOn
Indicates that one entity provides or holds a scholarship related to another entity, such as a person receiving financial support for study at an institution or in a specific field.
-
E.
associatedWithScholarshipField
Indicates that an entity has a connection or relevance to a particular field or area of scholarship.
- 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_69f76e80f6f0819091cba8e19b269615 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fe38be079c8190a240191ac0e73e3a |
completed | May 8, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69fe350344508190930de2218156ca02 |
completed | May 8, 2026, 7:09 p.m. |
| PDg | Predicate description generation | batch_69fe38bc3e9c8190838430b22b82503f |
completed | May 8, 2026, 7:25 p.m. |
Created at: May 3, 2026, 4:13 p.m.