Triple
T37535616
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kanishka II |
E933186
|
entity |
| Predicate | hasNameInScholarship |
P200696
|
FINISHED |
| Object | Kanishka II |
—
|
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: Kanishka II | Statement: [Kanishka II, hasNameInScholarship, Kanishka II]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNameInScholarship Context triple: [Kanishka II, hasNameInScholarship, Kanishka II]
-
A.
hasAlternativeNameInScholarship
Indicates that an entity is known by a different name or label specifically within academic or scholarly contexts.
-
B.
hasTitleInScholarship
Indicates that an entity holds or is associated with a specific title within an academic or scholarly context.
-
C.
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.
-
D.
hasScholarships
Indicates that an entity provides, offers, or is associated with one or more scholarships to another entity.
-
E.
hasKeyThemeInScholarship
Indicates that a particular key theme is prominently present or emphasized within a body of scholarly work or research.
- 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_69f76ec999288190ae26ec7b6aea7046 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ffa15d53208190ab8574d6c7913e18 |
completed | May 9, 2026, 9:04 p.m. |
| PD | Predicate disambiguation | batch_69ff9eee681c81909434e79c627cb528 |
completed | May 9, 2026, 8:54 p.m. |
| PDg | Predicate description generation | batch_69ffa15c3f348190a59403bc72ac9ed4 |
completed | May 9, 2026, 9:04 p.m. |
Created at: May 3, 2026, 4:17 p.m.