Triple
T25597172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Military Lending Act |
E641685
|
entity |
| Predicate | MAPRIncludes |
P159460
|
FINISHED |
| Object | credit insurance premiums |
—
|
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: credit insurance premiums | Statement: [Military Lending Act, MAPRIncludes, credit insurance premiums]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: MAPRIncludes Context triple: [Military Lending Act, MAPRIncludes, credit insurance premiums]
-
A.
MAPRIncludes
Indicates that one map or mapping construct contains, encompasses, or incorporates another as part of its structure or content.
-
B.
MAPRIncludes
Indicates that one map or mapping construct contains, covers, or incorporates another as part of its scope or structure.
-
C.
includesMap
Indicates that one entity contains or incorporates another entity in the form of a map or mapping structure.
-
D.
mapsIncluded
Indicates that one map or mapping is contained within, or is a subset of, another map or mapping.
-
E.
hasMaps
Indicates that one entity possesses, includes, or provides access to one or more maps associated with another entity.
- 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_69e75dc60d108190b7e2419e36b0134b |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f9a420f08190a8ed8c9a8c245fc4 |
completed | May 2, 2026, 1:18 p.m. |
| PD | Predicate disambiguation | batch_69f4a0f7c6008190ae8cee3e71e19b94 |
completed | May 1, 2026, 12:47 p.m. |
| PDg | Predicate description generation | batch_69f55e497fa081909bc59a7b92c5df59 |
completed | May 2, 2026, 2:15 a.m. |
Created at: April 21, 2026, 4:28 p.m.