Triple
T15851023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Measure R |
E384336
|
entity |
| Predicate | earmarksFundsFor |
P72661
|
FINISHED |
| Object | specific transportation subprograms |
—
|
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: specific transportation subprograms | Statement: [Measure R, earmarksFundsFor, specific transportation subprograms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: earmarksFundsFor Context triple: [Measure R, earmarksFundsFor, specific transportation subprograms]
-
A.
funds
Indicates that one entity provides financial resources or monetary support to another entity or activity.
-
B.
fundingCharacteristics
Indicates the nature, terms, and key attributes of how something is funded or financially supported.
-
C.
fundingContext
Indicates the circumstances, purpose, or conditions under which funding is provided or used in a given relationship or action.
-
D.
fundingFocus
chosen
Indicates that one entity’s funding is directed toward or prioritized for a particular target, theme, or area of activity.
-
E.
Pillar IIFundingMechanism
Indicates a funding-related relationship under Pillar II, specifying how financial resources are provided, structured, or allocated within that pillar’s framework.
- 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_69d86da422088190aac39e32e6c68429 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e174de2cd48190ab18e48c9f051a2a |
completed | April 16, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69e142b976c081908d3ba3e705419f3a |
completed | April 16, 2026, 8:12 p.m. |
Created at: April 10, 2026, 4:50 a.m.