Triple
T1050779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York IRC |
E22692
|
entity |
| Predicate | usesInputFrom |
P19412
|
FINISHED |
| Object | U.S. Census data |
—
|
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: U.S. Census data | Statement: [New York IRC, usesInputFrom, U.S. Census data]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesInputFrom Context triple: [New York IRC, usesInputFrom, U.S. Census data]
-
A.
usesScientificInputFrom
Indicates that one entity bases its decisions, actions, or processes on scientific data, analysis, or expertise provided by another entity.
-
B.
input
chosen
Indicates that one entity provides data, signals, or resources that are received or processed by another entity.
-
C.
inputType
Indicates the kind or format of data that an entity expects to receive as input in a given context.
-
D.
usedWith
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
-
E.
isUsedAs
Indicates that one entity serves a particular function, role, or purpose as another entity.
- 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_69a493da02e081908c13ff5e02a0fe7a |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8b40d50819091cb37a2236e82ee |
completed | March 1, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69a4b7309cc481908ed839b0b8d75dbf |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.