Triple
T2633887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brazilian Grand Prix |
E59697
|
entity |
| Predicate | hasGrandstandFeature |
P42382
|
FINISHED |
| Object | close proximity of fans to track |
—
|
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: close proximity of fans to track | Statement: [Brazilian Grand Prix, hasGrandstandFeature, close proximity of fans to track]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGrandstandFeature Context triple: [Brazilian Grand Prix, hasGrandstandFeature, close proximity of fans to track]
-
A.
stadiumFeature
Indicates that a stadium possesses or includes a particular feature, characteristic, or facility.
-
B.
hasBackstageFacilities
Indicates that a venue or location provides backstage areas and related facilities for performers or staff.
-
C.
containsStadium
Indicates that a location or area includes a stadium within its boundaries or premises.
-
D.
hasStandingArea
Indicates that an entity includes or provides a designated area where people can stand.
-
E.
hasStand
Indicates that an entity possesses, is equipped with, or is supported by a stand or base structure.
- F. None of above. chosen
Provenance (4 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_69ab4ac8596c8190b34997e73d9e991c |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abdb0e7b888190bfa5d2e33f00ec0f |
completed | March 7, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69abd810d7f481908e81c305772c4c14 |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abdb0bf9b881908b239c1310c7bbf3 |
completed | March 7, 2026, 8 a.m. |
Created at: March 6, 2026, 9:50 p.m.