Triple
T17551028
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moët & Chandon |
E427462
|
entity |
| Predicate | alternateName |
P39
|
FINISHED |
| Object | Moët |
—
|
NE NERFINISHED |
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: Moët | Statement: [Moët & Chandon, alternateName, Moët]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moët Context triple: [Moët & Chandon, alternateName, Moët]
-
A.
Moët & Chandon
chosen
Moët & Chandon is a world-renowned French Champagne producer famous for its luxury sparkling wines and flagship Moët Impérial.
-
B.
Moët Hennessy
Moët Hennessy is a leading French producer and distributor of luxury wines and spirits, known for prestigious champagne and cognac brands.
-
C.
Pernod Ricard
Pernod Ricard is a major French wine and spirits company known globally for brands such as Absolut, Jameson, and Chivas Regal.
-
D.
Veuve Clicquot
Veuve Clicquot is a renowned French Champagne house famous for its premium sparkling wines and distinctive yellow label.
-
E.
Vittel
Vittel is a French spa town renowned for its mineral water springs and bottled water brand, located in northeastern France.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889df6dc081908f67dbadc03c07ee |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e454656dc08190bba85b93bd07b0a2 |
completed | April 19, 2026, 4:04 a.m. |
Created at: April 10, 2026, 5:50 a.m.