Triple
T709109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port Authority of New York and New Jersey |
E14166
|
entity |
| Predicate | hasTypeOfFunding |
P59
|
FINISHED |
| Object | tolls and user fees |
—
|
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: tolls and user fees | Statement: [Port Authority of New York and New Jersey, hasTypeOfFunding, tolls and user fees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfFunding Context triple: [Port Authority of New York and New Jersey, hasTypeOfFunding, tolls and user fees]
-
A.
funderType
Indicates the category or kind of organization or individual that provides funding in the relationship.
-
B.
fundedBy
Indicates that an entity receives financial support or resources from another entity.
-
C.
hasMonetaryGrant
Indicates that an entity provides or receives a monetary grant from another entity.
-
D.
fundingModel
chosen
Indicates how an entity is financially supported or sustained, such as through specific revenue sources, payment structures, or funding mechanisms.
-
E.
grantmakingType
Indicates the specific category or method by which grants are awarded or administered in a grantmaking relationship.
- 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_69a493494ec48190ae6751683625a9ba |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a5c011948190b2cfccd8fe722742 |
completed | March 1, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f0217081908268b3f47e72f8df |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:36 p.m.