Triple
T4977582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glass Stepping Stones |
E111804
|
entity |
| Predicate | riskStructure |
P15871
|
FINISHED |
| Object | binary choice at each step |
—
|
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: binary choice at each step | Statement: [Glass Stepping Stones, riskStructure, binary choice at each step]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: riskStructure Context triple: [Glass Stepping Stones, riskStructure, binary choice at each step]
-
A.
riskModel
Indicates a relationship where an entity serves as or is associated with a model used to assess, quantify, or manage risk for another entity or situation.
-
B.
riskType
chosen
Indicates the category or nature of risk associated with an entity, event, or relationship.
-
C.
riskBasis
Indicates the underlying factor, condition, or rationale that forms the basis for assessing or assigning risk in a given context.
-
D.
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.
-
E.
riskTaken
Indicates that an entity has undertaken an action or decision involving exposure to potential loss, harm, or uncertainty.
- 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_69bd441adc208190b70a033a0741d01e |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd730a7590819088ab8d49c5c88c2f |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd7146e6e881908a55ab2756b631f6 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:33 p.m.