Triple
T37758112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Interstate 35 in Austin, Texas |
E941175
|
entity |
| Predicate | noiseImpact |
P167197
|
FINISHED |
| Object | traffic noise affecting adjacent neighborhoods |
—
|
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: traffic noise affecting adjacent neighborhoods | Statement: [Interstate 35 in Austin, Texas, noiseImpact, traffic noise affecting adjacent neighborhoods]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: noiseImpact Context triple: [Interstate 35 in Austin, Texas, noiseImpact, traffic noise affecting adjacent neighborhoods]
-
A.
noiseLevel
Indicates the intensity or amount of sound present in a given environment or from a specific source.
-
B.
noiseFootprint
chosen
Indicates the extent and distribution of noise generated by a source over a surrounding area or environment.
-
C.
noiseCompliance
Indicates that an entity adheres to specified rules or standards governing acceptable noise levels or sound emissions.
-
D.
disturbanceLevel
Indicates the degree or intensity of disruption, interference, or deviation from a normal or stable state in a given context.
-
E.
windImpact
Indicates the influence or effect that wind has on an entity, condition, or process.
- 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_69f76ee1f3a88190834e6c8af99bccc9 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbaef7b6c48190b99d82da5594889c |
completed | May 6, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69fbadf632ec8190b14991c971258307 |
completed | May 6, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:19 p.m.