Triple
T9589660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Congestion Mitigation and Air Quality Improvement Program |
E231383
|
entity |
| Predicate | targetsAreaType |
P68386
|
FINISHED |
| Object | nonattainment areas |
—
|
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: nonattainment areas | Statement: [Congestion Mitigation and Air Quality Improvement Program, targetsAreaType, nonattainment areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetsAreaType Context triple: [Congestion Mitigation and Air Quality Improvement Program, targetsAreaType, nonattainment areas]
-
A.
targetArea
Indicates the specific area or region that is the intended focus or destination of an action or effect.
-
B.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
C.
includesAreaType
Indicates that one entity encompasses or contains another entity of a specified area type within its scope or boundaries.
-
D.
typeOfAreaRepresented
Indicates that one entity specifies the kind or category of area that another entity represents.
-
E.
areaServedType
chosen
Indicates the type or category of area that is served by an entity or service.
- 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_69ca8482884481908eccdfdf64d6fbf7 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd99f1696c8190addf1a43544f2c18 |
completed | April 1, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_69ccd59fd7408190b36831902e3f37f7 |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:06 p.m.