Triple
T36169868
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NASA appropriations acts |
E1046115
|
entity |
| Predicate | temporalApplicability |
P51711
|
FINISHED |
| Object | one fiscal year |
—
|
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: one fiscal year | Statement: [NASA appropriations acts, temporalApplicability, one fiscal year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: temporalApplicability Context triple: [NASA appropriations acts, temporalApplicability, one fiscal year]
-
A.
hasTemporalUse
chosen
Indicates that something is used, applicable, or valid only during a specific time or temporal interval.
-
B.
temporalImplication
Indicates that the occurrence or truth of one event or condition implies the later occurrence or truth of another, with an explicit ordering in time.
-
C.
temporalAspect
Indicates the time-related characteristics or phase (such as duration, frequency, or temporal status) associated with an event or relationship.
-
D.
temporal scope
Indicates the time period or duration over which a particular relationship, condition, or fact holds true.
-
E.
temporality
Indicates the time-related relationship between events or states, such as their order, duration, or simultaneity.
- 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_69f76e396bc88190b99d221bff9be27a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b69b333081909cadbed3fcb8ecf5 |
completed | May 3, 2026, 8:56 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c2a5f8819094ad4621d7b97e0c |
completed | May 3, 2026, 8:49 p.m. |
Created at: May 3, 2026, 4:08 p.m.