Triple
T365735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Defense Authorization Act for Fiscal Year 2020 |
E7955
|
entity |
| Predicate | sectionIncludes |
P1393
|
FINISHED |
| Object | Section 1601 |
—
|
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: Section 1601 | Statement: [National Defense Authorization Act for Fiscal Year 2020, sectionIncludes, Section 1601]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sectionIncludes Context triple: [National Defense Authorization Act for Fiscal Year 2020, sectionIncludes, Section 1601]
-
A.
section
Indicates that one entity is a distinct part, division, or segment of another entity within a larger whole.
-
B.
includes
chosen
Indicates that one entity contains, encompasses, or has another entity as a part, member, or subset.
-
C.
section7Provides
Indicates that Section 7 serves as the source or provider of something (such as rights, obligations, benefits, or content) to another party or element.
-
D.
notableSection
Indicates that a particular part or segment of something is especially important, prominent, or worthy of attention within the whole.
-
E.
isSectionNumber
Indicates that one entity is the section number identifier associated with another entity, typically within a structured document or text.
- 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_69a2e7e880008190a6ad7e06e5d03007 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebe7d4d0819083daeb7686ae1914 |
completed | Feb. 28, 2026, 1:21 p.m. |
| PD | Predicate disambiguation | batch_69a2e95dbb208190b277fc5352a4ee84 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.