Triple
T2734486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexey |
E60595
|
entity |
| Predicate | isCognateWith |
P2527
|
FINISHED |
| Object | Alexis |
E90901
|
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: Alexis | Statement: [Alexey, isCognateWith, Alexis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alexis Context triple: [Alexey, isCognateWith, Alexis]
-
A.
Alexis
chosen
Alexis is a given name most famously borne by the French political thinker and historian Alexis de Tocqueville.
-
B.
Alix
Alix is the given name of Alix of Hesse and by Rhine, who became Empress Alexandra Feodorovna of Russia as the wife of Tsar Nicholas II.
-
C.
Alexis Morris
Alexis Morris is an American college basketball guard best known for starring at LSU and playing a pivotal role in the team’s 2023 national championship run.
-
D.
Arielle
Arielle is a given name shared by various individuals, including Arielle Zuckerberg, a venture capitalist and younger sister of Meta co-founder Mark Zuckerberg.
-
E.
Antoinette
Antoinette is a feminine given name of French origin, historically associated with nobility and later borne by various notable figures in the arts and public life.
- 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_69ab4b77febc819095603eb012cd141b |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb0e7b888190bfa5d2e33f00ec0f |
completed | March 7, 2026, 8 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afb6a15e548190a118880f9904f9cc |
completed | March 10, 2026, 6:13 a.m. |
Created at: March 6, 2026, 9:56 p.m.