Triple
T3266047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lorraine |
E68529
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Épinal |
E391263
|
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: Épinal | Statement: [Lorraine, containsCity, Épinal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Épinal Context triple: [Lorraine, containsCity, Épinal]
-
A.
Épinal
chosen
Épinal is a historic town in northeastern France, known for its traditional image-printing industry and picturesque setting in the Vosges region.
-
B.
Besançon
Besançon is a historic city in eastern France, known for its well-preserved Vauban fortifications, rich cultural heritage, and role as a regional administrative and educational center.
-
C.
Montélimar
Montélimar is a town in southeastern France, known as the "gateway to Provence" and famous for its traditional nougat confectionery.
-
D.
Brioude
Brioude is a historic town in south-central France known for its Romanesque Basilica of Saint-Julien and its location in the Haute-Loire department of the Auvergne region.
-
E.
Tournus
Tournus is a historic town in eastern France’s Burgundy region, known for its Romanesque abbey and riverside setting along the Saône.
- 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_69ad8590444081909e8107a8aeef3a23 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adafcc99908190897230b4b71e2ea8 |
completed | March 8, 2026, 5:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b511f9d8dc8190bc3728e75dec1059 |
completed | March 14, 2026, 7:44 a.m. |
Created at: March 8, 2026, 3:09 p.m.