Triple
T12342823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stéphane Gsell |
E294271
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Gsell |
E294271
|
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: Gsell | Statement: [Stéphane Gsell, familyName, Gsell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gsell Context triple: [Stéphane Gsell, familyName, Gsell]
-
A.
Gsell
chosen
Gsell is a surname of Germanic origin borne by various notable individuals, including artists, scholars, and public figures.
-
B.
Gavisse
Gavisse is a small commune in northeastern France, located in the Moselle department near the border with Luxembourg and Germany.
-
C.
Geva
Geva is a surname most notably associated with Tamara Geva, a Russian-American actress, dancer, and choreographer.
-
D.
Balzar
Balzar is a town and agricultural center in coastal Ecuador, known for its rice and banana production within Guayas Province.
-
E.
Gaume
Gaume is a culturally distinct region in southern Belgium known for its milder microclimate, French-speaking population, and characteristic rural landscapes.
- 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_69d6ab6ccbec8190b09e2d357aa80064 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f78a970819086beec3e4da8c49e |
completed | April 10, 2026, 6:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62aaa1d548190be065412aab70385 |
completed | May 2, 2026, 4:47 p.m. |
Created at: April 8, 2026, 9:53 p.m.