Triple
T12016094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gino |
E286028
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Geno |
E177675
|
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: Geno | Statement: [Gino, hasVariant, Geno]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Geno Context triple: [Gino, hasVariant, Geno]
-
A.
Geno
chosen
Geno is the widely used nickname of Hall of Fame University of Connecticut women's basketball coach Geno Auriemma.
-
B.
Geneta
Geneta is a residential district and suburb within Södertälje Municipality in Sweden.
-
C.
Genetz
Genetz is a Finnish surname most notably associated with Arvid Genetz, a 19th-century linguist, poet, and politician.
-
D.
Genn
Genn is a surname most notably associated with British actor and barrister Leo Genn.
-
E.
Gena
Gena is a Russian diminutive form of the male given name Gennady, commonly used as an informal or affectionate nickname.
- 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_69d6ab45a368819084fce08bf0dc3705 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903d9b17881908894be80d7c1b64e |
completed | April 10, 2026, 2:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f48b53cd08819084a9335449844f12 |
completed | May 1, 2026, 11:15 a.m. |
Created at: April 8, 2026, 9:47 p.m.