Triple
T11308683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeanie |
E267780
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Jeaniee |
E881536
|
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: Jeaniee | Statement: [Jeanie, hasVariant, Jeaniee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeaniee Context triple: [Jeanie, hasVariant, Jeaniee]
-
A.
Jennie-O
Jennie-O is a major American food brand best known for its turkey products, including fresh, frozen, and processed turkey items.
-
B.
Qeelin
Qeelin is a contemporary fine jewelry brand known for blending Chinese cultural symbolism with modern design, operating as part of the French luxury group Kering.
-
C.
Tifanie
chosen
Tifanie is a given name, typically a feminine variant of the name Tiffany.
-
D.
Caroline Kava
Caroline Kava is an American actress and playwright known for her supporting roles in film and television, particularly in dramas of the 1980s and 1990s.
-
E.
La Suze
La Suze is a French bitter apéritif made from gentian root and other botanicals, known for its bright yellow color and distinctive, slightly herbal flavor.
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9bf87d88190904c2d174578ebbf |
completed | April 9, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e50a70022081908bc74185003a3503 |
completed | April 19, 2026, 5:01 p.m. |
Created at: April 8, 2026, 9:32 p.m.