Triple
T47610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nansen Refugee Award |
E935
|
entity |
| Predicate | namedAfterOccupation |
P365
|
FINISHED |
| Object | Norwegian explorer |
—
|
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 explorer | Statement: [Nansen Refugee Award, namedAfterOccupation, Norwegian explorer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namedAfterOccupation Context triple: [Nansen Refugee Award, namedAfterOccupation, Norwegian explorer]
-
A.
namesakeOccupation
chosen
Indicates that one entity’s occupation is the same as, or derived from, the occupation associated with the other entity’s namesake.
-
B.
namedAfter
Indicates that one entity has been given its name in honor of, or derived from, another entity.
-
C.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
D.
careerStart
Indicates the point in time when an entity begins its professional career or main occupational activity.
-
E.
authorOccupation
Indicates the professional role or job that an author holds or is associated with.
- 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_69a2480baefc81909951b14058479aa2 |
completed | Feb. 28, 2026, 1:42 a.m. |
| NER | Named-entity recognition | batch_69a24c1a5c14819088748317a3f262c8 |
completed | Feb. 28, 2026, 1:59 a.m. |
| PD | Predicate disambiguation | batch_69a24abe7cb481908d969e54032f6c75 |
completed | Feb. 28, 2026, 1:54 a.m. |
Created at: Feb. 28, 2026, 1:47 a.m.