Triple
T571755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Alabama |
E13676
|
entity |
| Predicate | residentialCampus |
P16150
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [University of Alabama, residentialCampus, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: residentialCampus Context triple: [University of Alabama, residentialCampus, yes]
-
A.
cityCampus
Indicates that a campus is located within or associated with a particular city.
-
B.
campus
Indicates that an entity is located on, associated with, or taking place within a particular campus.
-
C.
campusType
Indicates the classification or category of a campus based on its type (e.g., main, satellite, urban, rural).
-
D.
campusArea
Indicates that one entity is the physical area or spatial extent of a campus associated with another entity.
-
E.
hostsCampusOf
Indicates that one entity serves as the physical location or site where another entity’s campus is situated or maintained.
- 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_69a4933fa4d88190a7949cc83c08c5c1 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49b483ac08190b3be152a7cf42011 |
completed | March 1, 2026, 8:02 p.m. |
| PD | Predicate disambiguation | batch_69a494c2caac819086ab316fa49d324c |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a498dd579081908e02368a4c5efc8c |
completed | March 1, 2026, 7:51 p.m. |
Created at: March 1, 2026, 7:33 p.m.