Triple
T21024269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deshay |
E517895
|
entity |
| Predicate | hasSpellingVariant |
P457
|
FINISHED |
| Object | Deshay |
—
|
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: Deshay | Statement: [Deshay, hasSpellingVariant, Deshay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Deshay Context triple: [Deshay, hasSpellingVariant, Deshay]
-
A.
Deshay
chosen
Deshay is a variant transliteration of the Indian surname "Desai," commonly associated with communities in western India.
-
B.
Deshays
Deshays is a French surname most notably associated with the 18th-century painter Jean-Baptiste Deshays.
-
C.
Houyet
Houyet is a rural municipality in the province of Namur, Belgium, known for its forests, castles, and location along the Lesse River.
-
D.
Dagneux
Dagneux is a commune in eastern France’s Ain department, known for its residential character and proximity to the Lyon metropolitan area.
-
E.
Daunou
Daunou is a French surname most notably borne by Pierre-Claude-François Daunou, an influential historian, archivist, and statesman of the French Revolution and Napoleonic era.
- 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_69e0b50262b081909bc488937145eb73 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc5f5bcc8190ab5fcc467703f0ef |
completed | April 21, 2026, 4:26 a.m. |
Created at: April 16, 2026, 1:55 p.m.