Triple
T4075468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sportpark Ronhof Thomas Sommer |
E86753
|
entity |
| Predicate | hasStandType |
P31102
|
FINISHED |
| Object | seated stands |
—
|
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: seated stands | Statement: [Sportpark Ronhof Thomas Sommer, hasStandType, seated stands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStandType Context triple: [Sportpark Ronhof Thomas Sommer, hasStandType, seated stands]
-
A.
hasStandsType
chosen
Indicates that an entity has or is associated with a particular type or category of stands (e.g., display stands, support stands, or similar structures).
-
B.
hasStand
Indicates that an entity possesses, is equipped with, or is supported by a stand or base structure.
-
C.
hasSternType
Indicates that an entity (typically a vessel) possesses a specific type or design of stern.
-
D.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
-
E.
hasBenchType
Indicates that an entity is associated with or characterized by a specific type or category of bench.
- 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_69aed93ebe448190a1f1686e28740ac9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefc25e2e08190b3c048e1b8f85bbf |
completed | March 9, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69aef9082c2081908474f082a49bebc8 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:39 p.m.