Triple
T17339248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lærdal Tunnel |
E421020
|
entity |
| Predicate | hasMobilePhoneCoverage |
P46630
|
FINISHED |
| Object | partial |
—
|
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: partial | Statement: [Lærdal Tunnel, hasMobilePhoneCoverage, partial]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMobilePhoneCoverage Context triple: [Lærdal Tunnel, hasMobilePhoneCoverage, partial]
-
A.
hasCellService
chosen
Indicates that a location, device, or area is within range of a cellular network and can access mobile phone or data services.
-
B.
hasCellularModel
Indicates that one entity serves as a cellular (cell-based) model or system used to study, represent, or simulate the biological properties or behavior of another entity.
-
C.
hasCellularComponent
Indicates that an entity possesses, includes, or is associated with a specific cellular component as part of its structure or organization.
-
D.
hasTelephoneService
Indicates that a subject is provided with or connected to telephone service.
-
E.
hasMVNO
Indicates that one entity operates as a Mobile Virtual Network Operator (MVNO) using the network infrastructure or services provided by another entity.
- 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_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. |
Created at: April 10, 2026, 5:44 a.m.