Triple
T421479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trinity College |
E8111
|
entity |
| Predicate | campusFeature |
P2465
|
FINISHED |
| Object | historic quadrangle |
—
|
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: historic quadrangle | Statement: [Trinity College, campusFeature, historic quadrangle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: campusFeature Context triple: [Trinity College, campusFeature, historic quadrangle]
-
A.
hasCampusFeature
chosen
Indicates that a campus possesses or includes a specific physical or functional feature.
-
B.
campus
Indicates that an entity is located on, associated with, or taking place within a particular campus.
-
C.
cityCampus
Indicates that a campus is located within or associated with a particular city.
-
D.
campusArea
Indicates that one entity is the physical area or spatial extent of a campus associated with another entity.
-
E.
campusType
Indicates the classification or category of a campus based on its type (e.g., main, satellite, urban, rural).
- 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_69a2e7f1d1bc81909cf2dc9754a3c334 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eec0e9dc81908c08b209ce5278ef |
completed | Feb. 28, 2026, 1:33 p.m. |
| PD | Predicate disambiguation | batch_69a2edd3b948819097d96c73d0a0f699 |
completed | Feb. 28, 2026, 1:29 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.