Triple
T15835844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asset Guarantee Program |
E383981
|
entity |
| Predicate | assetTypeCovered |
P15055
|
FINISHED |
| Object | mortgage-related assets |
—
|
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: mortgage-related assets | Statement: [Asset Guarantee Program, assetTypeCovered, mortgage-related assets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: assetTypeCovered Context triple: [Asset Guarantee Program, assetTypeCovered, mortgage-related assets]
-
A.
assetType
chosen
Indicates the specific category or classification of an asset within a broader asset framework or system.
-
B.
typicallyCovers
Indicates that one entity is the kind of thing that usually or normally includes, addresses, or encompasses another entity.
-
C.
typeOfCoverage
Indicates the specific kind or category of coverage that applies in a given context (such as insurance, service, or protection).
-
D.
typeOfDiscriminationCovered
Indicates that a particular kind or category of discriminatory behavior is included within the scope of protections, rules, or analysis.
-
E.
collectivelyCovers
Indicates that a group of entities, taken together, fully covers or accounts for a specified set, area, or scope.
- 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_69d86da34c888190976e06c4019d415a |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e142e0e1cc8190851b30b03cf9c9b8 |
completed | April 16, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69e005418f588190824d91ff7974dada |
completed | April 15, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:49 a.m.