Triple
T1628498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mueller |
E35200
|
entity |
| Predicate | isEquivalentSurnameInLanguage |
P27865
|
FINISHED |
| Object | Meunier (French) |
E115887
|
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: Meunier (French) | Statement: [Mueller, isEquivalentSurnameInLanguage, Meunier (French)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meunier (French) Context triple: [Mueller, isEquivalentSurnameInLanguage, Meunier (French)]
-
A.
The French
The French is a renowned fine-dining restaurant in Manchester’s Midland Hotel, known for its modern British cuisine and historic, elegant setting.
-
B.
Calaisienne
Calaisienne is the French term for a female inhabitant or native of the port city of Calais in northern France.
-
C.
Viennois
Viennois is the French term for an inhabitant or native of the city of Vienne in southeastern France.
-
D.
Boulanger
chosen
Boulanger is the French term for a baker, a person who professionally prepares and bakes bread and other baked goods.
-
E.
Maybeck
Maybeck is the surname of Bernard Maybeck, an influential American architect known for his innovative and eclectic designs in the early 20th century, particularly in the San Francisco Bay Area.
- 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_69a886036bc081909ff5de16dbe5e8ea |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa61df32a88190a7e823a77bdcc84a |
completed | March 6, 2026, 5:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad58d5acd8819090c51678ce0f63f0 |
completed | March 8, 2026, 11:09 a.m. |
Created at: March 4, 2026, 7:28 p.m.