Triple
T596709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Levi |
E11399
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Levie |
E75258
|
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: Levie | Statement: [Levi, hasVariant, Levie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Levie Context triple: [Levi, hasVariant, Levie]
-
A.
Levy
chosen
Levy is a variant spelling of the name Levi, commonly used as a Jewish surname and sometimes as a given name.
-
B.
Lev
Lev is the Russian given name of the renowned writer Leo Tolstoy, under which he was known in his native language.
-
C.
Levi
Levi is the surname of Primo Levi, the renowned Italian Jewish chemist and writer best known for his memoirs about surviving the Auschwitz concentration camp.
-
D.
Levi
Levi is a biblical patriarch, one of the twelve sons of Jacob and ancestor of the Israelite tribe of Levi, traditionally associated with priestly duties.
-
E.
Beni
Beni is a sparsely populated, largely Amazonian department in northeastern Bolivia known for its tropical lowlands, cattle ranching, and rich indigenous cultures.
- 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_69a4932779b881908688590d59c71900 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49d2b98d08190a1c1e8659efdfd75 |
completed | March 1, 2026, 8:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5238759c88190b1a960291c758447 |
completed | March 2, 2026, 5:43 a.m. |
Created at: March 1, 2026, 7:35 p.m.