Triple
T17657092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princess Martha Coast |
E440152
|
entity |
| Predicate | hasLanguageOfExploration |
P128417
|
FINISHED |
| Object | Norwegian |
—
|
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: Norwegian | Statement: [Princess Martha Coast, hasLanguageOfExploration, Norwegian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageOfExploration Context triple: [Princess Martha Coast, hasLanguageOfExploration, Norwegian]
-
A.
hasExploration
Indicates that one entity engages in, is associated with, or possesses an activity or process of exploration in relation to another entity or context.
-
B.
hasLanguageInUniverse
Indicates that a particular language exists or is used within a specified fictional or conceptual universe.
-
C.
hasLanguageOfStudy
Indicates that an entity studies or is engaged in learning a particular language.
-
D.
hasLanguageSphere
Indicates that one entity falls within the linguistic influence, usage domain, or coverage area defined by another entity’s language.
-
E.
hasNotableRegionOfExploration
Indicates that an entity is associated with a specific geographic or conceptual region where its exploration activities are particularly significant or noteworthy.
- 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_69d8b9e87e18819087104a44dc4dc5b1 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46ea2b3308190b9ad752728d98856 |
completed | April 19, 2026, 5:56 a.m. |
| PD | Predicate disambiguation | batch_69e3cddc87188190ac2f049b86038676 |
completed | April 18, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69e3cfaac2b881909e1140339eb1a0dd |
completed | April 18, 2026, 6:38 p.m. |
Created at: April 10, 2026, 9:27 a.m.