Triple
T13426302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rally Argentina |
E313489
|
entity |
| Predicate | safetyChallenges |
P82346
|
FINISHED |
| Object | high spectator numbers |
—
|
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: high spectator numbers | Statement: [Rally Argentina, safetyChallenges, high spectator numbers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyChallenges Context triple: [Rally Argentina, safetyChallenges, high spectator numbers]
-
A.
safetyChallenge
chosen
Indicates that one entity presents or poses a safety-related test, risk, or concern to another entity.
-
B.
safety
Indicates that an entity provides, ensures, or is associated with protection from harm, danger, or risk for another entity or within a given context.
-
C.
safetyImplication
Indicates that one entity has a consequence, effect, or relevance for the safety or risk level associated with another entity or situation.
-
D.
safetyCategory
Indicates the classification of something according to its level or type of safety.
-
E.
safetyPoints
Indicates a relationship where an entity is assigned or associated with a measure of safety, typically quantified as points reflecting its safety level or performance.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaed1f9208190bf5ef5b8a7ded376 |
completed | April 12, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a03926188190ab3948d1f5d3941f |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:40 p.m.