Triple
T10166728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | College Walk |
E235221
|
entity |
| Predicate | campusZoning |
P31311
|
FINISHED |
| Object | central campus axis |
—
|
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: central campus axis | Statement: [College Walk, campusZoning, central campus axis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: campusZoning Context triple: [College Walk, campusZoning, central campus axis]
-
A.
campusArea
Indicates that one entity is the physical area or spatial extent of a campus associated with another entity.
-
B.
campusUse
Indicates that something is intended for, associated with, or occurring in the use or activities of a campus or campus community.
-
C.
cityCampus
Indicates that a campus is located within or associated with a particular city.
-
D.
campusAreaType
chosen
Indicates the classification of a campus area according to its type or functional category.
-
E.
campusCluster
Indicates a relationship where multiple campus locations or facilities are grouped or associated together as part of the same cluster or complex.
- 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_69ca84ceafd0819085828600e11bed6b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdec6e016c81909ded2a16b839c405 |
completed | April 2, 2026, 4:11 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba9956c8190a3e15d091e33149d |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:10 p.m.