Triple
T33212246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 99942 Apophis |
E850190
|
entity |
| Predicate | riskScalePreviously |
P176199
|
FINISHED |
| Object | 4 on Torino Scale (now 0) |
—
|
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: 4 on Torino Scale (now 0) | Statement: [99942 Apophis, riskScalePreviously, 4 on Torino Scale (now 0)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: riskScalePreviously Context triple: [99942 Apophis, riskScalePreviously, 4 on Torino Scale (now 0)]
-
A.
riskLevel
Indicates the degree of potential harm, loss, or adverse outcome associated with a particular situation, action, or entity.
-
B.
riskType
Indicates the category or nature of risk associated with an entity, event, or relationship.
-
C.
riskFeature
Indicates that one entity possesses or exhibits a characteristic, condition, or attribute that increases the likelihood or severity of a negative outcome for another entity or situation.
-
D.
riskBasis
Indicates the underlying factor, condition, or rationale that forms the basis for assessing or assigning risk in a given context.
-
E.
riskTaken
Indicates that an entity has undertaken an action or decision involving exposure to potential loss, harm, or uncertainty.
- 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_69f3495fb92c819083ce65d0ddee7a76 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6dd3cc0648190a275812d6711275a |
completed | May 3, 2026, 5:29 a.m. |
| PD | Predicate disambiguation | batch_69f6d82eaee081908f06a71546315aea |
completed | May 3, 2026, 5:07 a.m. |
| PDg | Predicate description generation | batch_69f6dd3b335481909e24d4eb5b0269f9 |
completed | May 3, 2026, 5:29 a.m. |
Created at: May 1, 2026, 1:30 a.m.