Triple
T16403987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heyendaal campus |
E398375
|
entity |
| Predicate | hasSportsFacilitiesNearby |
P68166
|
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: [Heyendaal campus, hasSportsFacilitiesNearby, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSportsFacilitiesNearby Context triple: [Heyendaal campus, hasSportsFacilitiesNearby, yes]
-
A.
hasNearbyStadium
Indicates that one entity is located close to or in the vicinity of a stadium associated with another entity.
-
B.
hasRecreationFacility
Indicates that one entity provides, contains, or is equipped with a recreational facility for use by another entity or by the public.
-
C.
hasRecreationalUseNearby
chosen
Indicates that there is at least one location or facility for recreational activities situated close to the referenced entity.
-
D.
hasAttractionNearby
Indicates that one entity is located close to another entity that serves as an attraction or point of interest.
-
E.
hasLocalSport
Indicates that a place or community is associated with, supports, or regularly engages in a particular sport at the local level.
- 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_69d87f2950248190bc8ad9b9bebdc8c8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e327d12dc08190a5b497692b667ed7 |
completed | April 18, 2026, 6:42 a.m. |
| PD | Predicate disambiguation | batch_69e226fe1dd08190865c181721f8c348 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:09 a.m.