Triple
T26034016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cross-State Air Pollution Rule |
E647504
|
entity |
| Predicate | targetsEffect |
P58916
|
FINISHED |
| Object | fine particulate matter (PM2.5) |
—
|
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: fine particulate matter (PM2.5) | Statement: [Cross-State Air Pollution Rule, targetsEffect, fine particulate matter (PM2.5)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetsEffect Context triple: [Cross-State Air Pollution Rule, targetsEffect, fine particulate matter (PM2.5)]
-
A.
attackEffect
Indicates that one entity’s attack produces a specific effect or consequence on another entity.
-
B.
tierEffect
Indicates how belonging to a particular tier influences or modifies the outcome, behavior, or properties associated with that tier.
-
C.
effectOnOthers
chosen
Indicates the impact or influence that one entity’s actions, presence, or state has on other entities.
-
D.
target
Indicates that one entity is the intended object, goal, or focus of another entity’s action or attention.
-
E.
hasEffectIn
Indicates that one entity produces, causes, or exerts an effect within a specified context, system, or environment.
- 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_69e77e8b60e88190a3b26c4f0032a2c2 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f6978fe97081908fe568091ad9b159 |
completed | May 3, 2026, 12:32 a.m. |
| PD | Predicate disambiguation | batch_69f69661e6ec8190948251c7516a32ad |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 22, 2026, 9:06 a.m.