Triple
T22917316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kevin Rosier |
E568767
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Rosier |
—
|
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: Rosier | Statement: [Kevin Rosier, familyName, Rosier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rosier Context triple: [Kevin Rosier, familyName, Rosier]
-
A.
Rosier
chosen
Rosier is a surname of French origin borne by various notable individuals across different fields.
-
B.
Rosera
Rosera is a town in the Samastipur district of Bihar, India, known as a local commercial and administrative center.
-
C.
Rosa gallica
Rosa gallica is a species of wild rose native to Europe and western Asia, historically cultivated for its fragrant flowers and use in perfumery and medicine.
-
D.
Rosa Gryphus
Rosa Gryphus is a central character in Alexandre Dumas' novel "The Black Tulip," known for her devotion, courage, and pivotal role in aiding the protagonist amid political intrigue.
-
E.
Rosa
Rosa is a feminine given name of Latin origin meaning "rose," used in many languages and cultures.
- 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_69e2458d90c88190a58cead4e781ca6a |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1807a14648190b5d5f7d926f19320 |
completed | April 29, 2026, 3:52 a.m. |
Created at: April 17, 2026, 3:42 p.m.