Triple
T23638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Cambridge |
E468
|
entity |
| Predicate | hasNobelLaureateAffiliation |
P324
|
FINISHED |
| Object | multiple Nobel Prize winners |
—
|
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: multiple Nobel Prize winners | Statement: [University of Cambridge, hasNobelLaureateAffiliation, multiple Nobel Prize winners]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNobelLaureateAffiliation Context triple: [University of Cambridge, hasNobelLaureateAffiliation, multiple Nobel Prize winners]
-
A.
hasNobelLaureatesAffiliated
chosen
Indicates that one entity has Nobel Prize laureates formally associated or connected with it (e.g., as members, staff, or alumni).
-
B.
hasAcademicAffiliation
Indicates that an entity is formally associated with an academic institution, such as through employment, enrollment, or official collaboration.
-
C.
notableScientist
Indicates that the subject is a scientist who is widely recognized for significant contributions or impact in their field.
-
D.
hasAlumni
Indicates that an institution or organization is associated with individuals who formerly attended or graduated from it.
-
E.
hasAcademicStaff
Indicates that an institution or organization employs or is associated with one or more academic staff members.
- F. None of above.
Provenance (3 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a246e94ca881908f7a7d2c0b293033 |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a246560af88190961ea00b35cf9388 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.