Triple
T241234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Ambient Air Quality Standards |
E4935
|
entity |
| Predicate | attainmentAreaDefinedBy |
P9210
|
FINISHED |
| Object | meeting NAAQS |
—
|
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: meeting NAAQS | Statement: [National Ambient Air Quality Standards, attainmentAreaDefinedBy, meeting NAAQS]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: attainmentAreaDefinedBy Context triple: [National Ambient Air Quality Standards, attainmentAreaDefinedBy, meeting NAAQS]
-
A.
scopeOfAccreditation
Indicates the specific range, domains, or activities for which an entity’s accreditation or formal recognition is valid and applicable.
-
B.
hasCatchmentArea
Indicates that a geographic or administrative unit serves as the area from which an entity (such as a facility or service) draws its users, resources, or influence.
-
C.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
D.
subDisciplineOf
Indicates that one discipline is a more specialized or narrower field within another, broader discipline.
-
E.
primaryLanguageOfInstruction
Indicates the language that is mainly used as the medium of teaching or instruction for a given educational context.
- F. None of above. chosen
Provenance (4 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25d35aa288190966b6e15af1525cb |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b60ad308190b12f119960a8bde7 |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25d3463648190ac716d7475378536 |
completed | Feb. 28, 2026, 3:12 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.