Triple
T15216940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lærdalsøyri |
E363659
|
entity |
| Predicate | hasNumberOfProtectedBuildings |
P42084
|
FINISHED |
| Object | over 150 protected wooden buildings |
—
|
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: over 150 protected wooden buildings | Statement: [Lærdalsøyri, hasNumberOfProtectedBuildings, over 150 protected wooden buildings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfProtectedBuildings Context triple: [Lærdalsøyri, hasNumberOfProtectedBuildings, over 150 protected wooden buildings]
-
A.
hasMunicipalBuildings
Indicates that a place or jurisdiction possesses one or more buildings used for municipal or local government functions.
-
B.
hasProtectedAreasNearby
Indicates that an entity is located close to one or more designated protected or conservation areas.
-
C.
hasPreservedBuildings
chosen
Indicates that an entity possesses buildings that have been maintained or kept in their original or historical condition.
-
D.
infrastructureProtected
Indicates that infrastructure is safeguarded or defended against damage, disruption, or unauthorized interference.
-
E.
hasNearbyCivicBuilding
Indicates that one entity is located close to, or in the immediate vicinity of, a civic building such as a government, public service, or community facility.
- 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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0076f90c481909989befe031a2cae |
completed | April 15, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69deca8479188190b2e5d3bc708d7d07 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:11 a.m.