Triple
T11692538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | COTS |
E277902
|
entity |
| Predicate | riskSharingModel |
P42253
|
FINISHED |
| Object | shared development risk between NASA and private companies |
—
|
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: shared development risk between NASA and private companies | Statement: [COTS, riskSharingModel, shared development risk between NASA and private companies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: riskSharingModel Context triple: [COTS, riskSharingModel, shared development risk between NASA and private companies]
-
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.
riskAllocation
chosen
Indicates how the potential negative consequences or uncertainties of an action, event, or agreement are distributed among the involved parties.
-
C.
riskMeasure
Indicates a quantitative assessment of the level of risk associated with an entity, event, 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.
riskType
Indicates the category or nature of risk associated with an entity, event, or relationship.
- 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_69d6aafe02d881909900d54ad7d4af84 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a47a3ddc819098e208611148d15b |
completed | April 10, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_69d88a7b30948190b616a9db5c5488d5 |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:40 p.m.