Triple
T17339235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lærdal Tunnel |
E421020
|
entity |
| Predicate | hasAirQualityMonitoring |
P127084
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Lærdal Tunnel, hasAirQualityMonitoring, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAirQualityMonitoring Context triple: [Lærdal Tunnel, hasAirQualityMonitoring, yes]
-
A.
environmentalMonitoring
Indicates the ongoing observation, measurement, and assessment of environmental conditions or changes, typically to detect impacts, trends, or compliance with standards.
-
B.
hasEnvironmentalQuality
Indicates that something possesses a particular environmental characteristic, condition, or attribute.
-
C.
hasTrafficMonitoring
Indicates that an entity is equipped with or associated with a system or capability for observing, measuring, or analyzing traffic conditions or flows.
-
D.
targetPollutant
Indicates that something is the specific pollutant that is being aimed at, affected, or addressed by an action, process, or regulation.
-
E.
hasPollutionIssue
Indicates that an entity is affected by, associated with, or characterized by a pollution-related problem or concern.
- 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_69d889d3adc881909319f1edb8d2a956 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a14ec90819098db2ac0d58a53e1 |
completed | April 19, 2026, 2:12 a.m. |
| PD | Predicate disambiguation | batch_69e3b021a5bc81909ae55406f9d0b37f |
completed | April 18, 2026, 4:24 p.m. |
| PDg | Predicate description generation | batch_69e3b2a225b08190a50f984caa6513b9 |
completed | April 18, 2026, 4:34 p.m. |
Created at: April 10, 2026, 5:44 a.m.