Triple
T8330271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donder |
E195056
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Donner |
E37300
|
NE 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: Donner | Statement: [Donder, alsoKnownAs, Donner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Donner Context triple: [Donder, alsoKnownAs, Donner]
-
A.
Donner
chosen
Donner is one of Santa Claus's traditional flying reindeer, often depicted as helping pull Santa’s sleigh on Christmas Eve.
-
B.
Karluk
Karluk refers to a historical branch of the Turkic peoples and their language group, influential in Central Asia during the early medieval period.
-
C.
George Donner
George Donner was an American pioneer and leader of the ill-fated Donner Party wagon train that became trapped in the Sierra Nevada during the winter of 1846–1847.
-
D.
Nanooks
Nanooks is the nickname for the University of Alaska Fairbanks athletic teams, representing the school in NCAA competition.
-
E.
Arviat
Arviat is a predominantly Inuit hamlet on the western shore of Hudson Bay in Nunavut, Canada, known for its traditional culture and remote Arctic setting.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca82e87f2c8190bdb71ee29dfc642d |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7fb995508190b2ca94ad45bf6d24 |
completed | March 31, 2026, 8:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd95c2c36481909793e9cd0c28168a |
completed | April 1, 2026, 10:01 p.m. |
Created at: March 30, 2026, 5:56 p.m.