Triple
T34636680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ArtEZ University of the Arts (Zwolle campus) |
E889445
|
entity |
| Predicate | hasCampusCityCharacteristic |
P145292
|
FINISHED |
| Object | medium-sized Dutch city |
—
|
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: medium-sized Dutch city | Statement: [ArtEZ University of the Arts (Zwolle campus), hasCampusCityCharacteristic, medium-sized Dutch city]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCampusCityCharacteristic Context triple: [ArtEZ University of the Arts (Zwolle campus), hasCampusCityCharacteristic, medium-sized Dutch city]
-
A.
hasCampusCity
Indicates that an educational institution or campus is located in a particular city.
-
B.
hasCampusTownCharacter
chosen
Indicates that a place exhibits qualities or atmosphere typically associated with a college or university town.
-
C.
hasCampusFeature
Indicates that a campus possesses or includes a specific physical or functional feature.
-
D.
hasCampusOn
Indicates that an institution or organization maintains a campus located on a specified geographic area or site.
-
E.
hasCampusCharacter
Indicates that an institution possesses a particular overall campus atmosphere, style, or defining quality.
- 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_69f349d724848190b63ad3407e0006d9 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff7595c9bc8190982c6e6e07a0c78f |
completed | May 9, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69ff715432a88190a25670d26614bde2 |
completed | May 9, 2026, 5:39 p.m. |
Created at: May 1, 2026, 2:04 a.m.