Triple
T13049444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gérard |
E327411
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Gérard (without accent in some contexts) |
E327411
|
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: Gérard (without accent in some contexts) | Statement: [Gérard, hasVariant, Gérard (without accent in some contexts)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gérard (without accent in some contexts) Context triple: [Gérard, hasVariant, Gérard (without accent in some contexts)]
-
A.
Gérard
chosen
Gérard is a French given name, equivalent to the Germanic name Gerhard, commonly used in French-speaking countries.
-
B.
Gérson
Gérson is a legendary Brazilian midfielder renowned for orchestrating play in Brazil’s iconic 1970 FIFA World Cup–winning team.
-
C.
Gerard
Gerard is a masculine given name of Germanic origin, commonly used in various European countries.
-
D.
Hervé
Hervé is a French given name, often considered a variant of the English name Harvey, and is commonly used for males in French-speaking regions.
-
E.
Stéphane
Stéphane is a French masculine given name, equivalent to Stephen in English, commonly used in Francophone countries.
- 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980b8811c81908577f092e2736610 |
completed | April 10, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6cbda9b548190a10a4835b2c75fdc |
completed | May 3, 2026, 4:15 a.m. |
Created at: April 9, 2026, 8:57 p.m.