Triple
T16631704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regenstein Library vicinity, University of Chicago |
E404094
|
entity |
| Predicate | campusRegion |
P21981
|
FINISHED |
| Object | north side of the main quadrangles |
—
|
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: north side of the main quadrangles | Statement: [Regenstein Library vicinity, University of Chicago, campusRegion, north side of the main quadrangles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: campusRegion Context triple: [Regenstein Library vicinity, University of Chicago, campusRegion, north side of the main quadrangles]
-
A.
campusArea
Indicates that one entity is the physical area or spatial extent of a campus associated with another entity.
-
B.
stateCampus
Indicates that a campus is part of, located within, or administered by a particular state.
-
C.
regionOfInstitution
chosen
Indicates that a specified region is the geographic area in which an institution is located or operates.
-
D.
cityCampus
Indicates that a campus is located within or associated with a particular city.
-
E.
cityCampusServes
Indicates that a city campus provides services, resources, or support to a particular population, area, or institution.
- 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_69d883897eb481909eaaa088ba9918d9 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e378e704c08190a28286ac12165ea5 |
completed | April 18, 2026, 12:28 p.m. |
| PD | Predicate disambiguation | batch_69e296ad3f148190af09223dc35b155c |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:17 a.m.