Triple
T749270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gonville and Caius College, Cambridge |
E15409
|
entity |
| Predicate | typeOfCollege |
P303
|
FINISHED |
| Object | mixed-gender college |
—
|
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: mixed-gender college | Statement: [Gonville and Caius College, Cambridge, typeOfCollege, mixed-gender college]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfCollege Context triple: [Gonville and Caius College, Cambridge, typeOfCollege, mixed-gender college]
-
A.
campusType
Indicates the classification or category of a campus based on its type (e.g., main, satellite, urban, rural).
-
B.
typeOfInstitution
chosen
Indicates the specific kind or category of institution that an entity belongs to or is classified as.
-
C.
college
Indicates that an entity is a college-level educational institution attended by or associated with another entity.
-
D.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
E.
university
Indicates that an educational institution of higher learning is associated with or attended by a given entity.
- 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_69a493599a0081908da65f3407af1ef2 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a6304e0c8190827fb57c5cac2da9 |
completed | March 1, 2026, 8:48 p.m. |
| PD | Predicate disambiguation | batch_69a4a5004f708190a984ee221716e19c |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.