Triple
T9800848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Autoroute A35 |
E237831
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Alsace region |
E19573
|
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: Alsace region | Statement: [Autoroute A35, serves, Alsace region]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alsace region Context triple: [Autoroute A35, serves, Alsace region]
-
A.
Alsace
chosen
Alsace is a historical and cultural region in northeastern France known for its blend of French and German influences, picturesque villages, and renowned wines.
-
B.
Alsacia
Alsacia is a Madrid Metro station on Line 2 serving the San Blas-Canillejas district in eastern Madrid, Spain.
-
C.
French Lorraine
French Lorraine is a historical region in northeastern France whose culture reflects a blend of French and Germanic influences.
-
D.
Jura region
The Jura region is a mountainous area in western Switzerland and eastern France known for its limestone plateaus, dense forests, watchmaking tradition, and distinctive wines and cheeses.
-
E.
Alsace-Lorraine
Alsace-Lorraine is a historically contested border region between France and Germany, known for its mixed cultural heritage and strategic importance in European conflicts.
- 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_69ca84dd4608819097ff4ed00feca280 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda62a11a88190880e0cce24923b14 |
completed | April 1, 2026, 11:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1cc53c3dc819084a4d8b72164a172 |
completed | April 5, 2026, 2:43 a.m. |
Created at: March 30, 2026, 8:29 p.m.