Triple
T5123579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aiken |
E115528
|
entity |
| Predicate | hasEtymologicalRelationTo |
P5801
|
FINISHED |
| Object | Aitken |
E18696
|
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: Aitken | Statement: [Aiken, hasEtymologicalRelationTo, Aitken]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aitken Context triple: [Aiken, hasEtymologicalRelationTo, Aitken]
-
A.
Aitken
Aitken is a large lunar impact crater on the Moon, best known as part of the immense South Pole–Aitken Basin on the Moon’s far side.
-
B.
Aitken
chosen
Aitken is a Scottish-origin surname notably borne by Max Aitken, 1st Baron Beaverbrook, a prominent Canadian-British newspaper magnate and politician.
-
C.
Atkinson
Atkinson is the surname of British comedian and actor Rowan Atkinson, best known for creating and portraying the character Mr. Bean.
-
D.
Bairstow
Bairstow is an English-origin surname borne by various notable figures in sports, politics, and the arts.
-
E.
Earley
Earley is a suburban town in Berkshire, England, situated near Reading and known for its residential character and proximity to major transport links.
- 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_69bd4442ade0819087b9461f892b206b |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd78045e448190961db0ca7692370e |
completed | March 20, 2026, 4:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bed9185b9481908afd32bdeefa3f1e |
completed | March 21, 2026, 5:44 p.m. |
Created at: March 20, 2026, 1:42 p.m.