Triple
T5206205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christ II |
E117515
|
entity |
| Predicate | hasScholarshipOn |
P62010
|
FINISHED |
| Object | authorship of Cynewulf |
—
|
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: authorship of Cynewulf | Statement: [Christ II, hasScholarshipOn, authorship of Cynewulf]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScholarshipOn Context triple: [Christ II, hasScholarshipOn, authorship of Cynewulf]
-
A.
hasScholarships
Indicates that an entity provides, offers, or is associated with one or more scholarships to another entity.
-
B.
hasOrganScholarships
Indicates that an entity offers or provides scholarships specifically related to organ study or performance.
-
C.
hasBursaries
Indicates that an entity provides or is associated with bursaries (financial aid or scholarships).
-
D.
hasFinancialAid
Indicates that one entity provides or is associated with financial assistance or support to another entity.
-
E.
associatedScholarship
Indicates a relationship where a scholarship is linked or connected to a particular entity (such as a person, program, or institution).
- 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_69bd4463dd3c81909966123f20b79d57 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7a490338819080481df79d3aae01 |
completed | March 20, 2026, 4:48 p.m. |
| PD | Predicate disambiguation | batch_69bd77bb4e8c819094b5ac7cf61512f9 |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd79000cf88190b3c05d95395b0cd2 |
completed | March 20, 2026, 4:42 p.m. |
Created at: March 20, 2026, 1:47 p.m.