Triple
T21353792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bitche canton |
E526557
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Philippsbourg |
—
|
NE NERFINISHED |
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: Philippsbourg | Statement: [Bitche canton, contains, Philippsbourg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Philippsbourg Context triple: [Bitche canton, contains, Philippsbourg]
-
A.
Philippsbourg
chosen
Philippsbourg is a small commune in northeastern France, situated in the Moselle department within the historical region of Lorraine.
-
B.
Philippsburg
Philippsburg is a historic town in southwestern Germany, known for its former fortress on the Rhine and its strategic military significance in early modern European wars.
-
C.
Diekirch
Diekirch is a town in northern Luxembourg known for its role in World War II, particularly during the country's liberation, and for its national military museum.
-
D.
Wissembourg
Wissembourg is a historic town in northeastern France’s Alsace region, known for its well-preserved medieval architecture and proximity to the German border.
-
E.
Dudelange
Dudelange is a town in southern Luxembourg known as one of the country’s larger industrial and residential centers near the French border.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b51cd5cc81909ac1187971e8a8ad |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69ee5bac9e1481909121e89f046c77f6 |
completed | April 26, 2026, 6:38 p.m. |
Created at: April 16, 2026, 5:05 p.m.