Triple
T8791798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean |
E209182
|
entity |
| Predicate | exampleCompoundName |
P85415
|
FINISHED |
| Object | Jean-Marie |
E435554
|
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: Jean-Marie | Statement: [Jean, exampleCompoundName, Jean-Marie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jean-Marie Context triple: [Jean, exampleCompoundName, Jean-Marie]
-
A.
Jean-Marie
chosen
Jean-Marie is a French given name most notably borne by Nobel Prize–winning chemist Jean-Marie Lehn.
-
B.
Jean-Louis
Jean-Louis is the given first name of the French Romantic painter Théodore Géricault, renowned for works such as "The Raft of the Medusa."
-
C.
Jean-Louis
Jean-Louis is the birth name of American novelist and Beat Generation icon Jack Kerouac.
-
D.
Jean Louis
Jean Louis was a renowned French-born American costume designer celebrated for his glamorous Hollywood film and television wardrobe creations.
-
E.
Jean Gras
Jean Gras was a mountaineer known for being among the first climbers to ascend the Breithorn in the Alps.
- 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_69ca836240888190a62b262e56a69d2f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f8e6e4881909155c40c52bc082c |
completed | March 31, 2026, 11:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfba0313d88190b646dbd34b5c424a |
completed | April 3, 2026, 1 p.m. |
Created at: March 30, 2026, 6:43 p.m.