Triple
T13590750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sephora |
E324685
|
entity |
| Predicate | foundingLocation |
P40
|
FINISHED |
| Object | Limoges, France |
E49689
|
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: Limoges, France | Statement: [Sephora, foundingLocation, Limoges, France]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Limoges, France Context triple: [Sephora, foundingLocation, Limoges, France]
-
A.
Limoges
chosen
Limoges is a historic city in central France renowned for its fine porcelain production and medieval architecture.
-
B.
Fontainebleau, France
Fontainebleau, France is a historic town southeast of Paris best known for its vast forest and royal château, long associated with French monarchs and outdoor recreation.
-
C.
Chatou, France
Chatou, France is a suburban town on the River Seine near Paris, historically known as an artists’ retreat associated with Impressionist and Fauvist painters.
-
D.
Blois, France
Blois, France is a historic city on the Loire River known for its Renaissance château and as the birthplace of King Stephen of England.
-
E.
Lestrem, France
Lestrem is a small commune in the Pas-de-Calais department of northern France, known for its rural character and local agricultural activities.
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb055cc98819091fab597b69e5e3e |
completed | April 12, 2026, 2:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f76bc578908190abd5cca94b1c3a5c |
completed | May 3, 2026, 3:37 p.m. |
Created at: April 9, 2026, 9:49 p.m.