Triple
T14667268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leidener Willeram |
E344410
|
entity |
| Predicate | scholarlyMilieu |
P115266
|
FINISHED |
| Object | medieval Leiden |
—
|
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: medieval Leiden | Statement: [Leidener Willeram, scholarlyMilieu, medieval Leiden]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scholarlyMilieu Context triple: [Leidener Willeram, scholarlyMilieu, medieval Leiden]
-
A.
scholarlyWork
Indicates a relationship where an entity is a formal academic or research work produced, published, or recognized within a scholarly context.
-
B.
scholarlyView
Indicates that one entity holds an academic or research-based interpretation, opinion, or theoretical stance about another entity.
-
C.
scholarlyUse
Indicates that something is used for academic, educational, or research-related purposes.
-
D.
scholarlyActivity
Indicates engagement in academic or research-related work, such as studying, teaching, publishing, or conducting scholarly inquiry.
-
E.
scholarlyEmphasis
Indicates a relationship where an entity focuses its academic attention, research, or analysis predominantly on a particular subject, theme, or area of study.
- 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_69d822e283fc8190a0e4c235cf880052 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb54dda1c8190bf16d17e26a2bba6 |
completed | April 14, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69de6576f0208190aa94d995e797ac38 |
completed | April 14, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69de716c17cc8190aeb85296abee85a7 |
completed | April 14, 2026, 4:55 p.m. |
Created at: April 10, 2026, 1:27 a.m.