Triple
T2616161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Bull Arena (Leipzig) |
E58891
|
entity |
| Predicate | hasTrainingFacilitiesNearby |
P5648
|
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: [Red Bull Arena (Leipzig), hasTrainingFacilitiesNearby, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrainingFacilitiesNearby Context triple: [Red Bull Arena (Leipzig), hasTrainingFacilitiesNearby, yes]
-
A.
hasNearbyMilitaryTrainingArea
Indicates that an entity is located close to a designated area used for military training activities.
-
B.
trainingFacilityLocation
Indicates the place or site where a training facility is situated or operates.
-
C.
hasNearbyInstitution
Indicates that one entity is located close to or in the immediate vicinity of an institution.
-
D.
hasNearbyFacility
chosen
Indicates that one entity is located close to or in the vicinity of a particular facility.
-
E.
hasFacilities
Indicates that an entity possesses, provides, or is equipped with certain facilities or physical resources.
- 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_69ab4ac444dc819099614e534dd6021f |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd89325308190985598373eb0d296 |
completed | March 7, 2026, 7:49 a.m. |
| PD | Predicate disambiguation | batch_69abd80cd7fc81909e9696db2919129f |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:50 p.m.