Triple
T8457467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MP 89 |
E199955
|
entity |
| Predicate | manufacturer |
P490
|
FINISHED |
| Object | CIMT Lorraine |
E387388
|
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: CIMT Lorraine | Statement: [MP 89, manufacturer, CIMT Lorraine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CIMT Lorraine Context triple: [MP 89, manufacturer, CIMT Lorraine]
-
A.
CIMT Lorraine
chosen
CIMT Lorraine is a French rolling stock manufacturer known for producing electric multiple units such as the Z 5600 series for the national railway network.
-
B.
Corine
Corine is a feminine given name used in various European countries, often considered a variant of "Corinne."
-
C.
French Lorraine
French Lorraine is a historical region in northeastern France whose culture reflects a blend of French and Germanic influences.
-
D.
Douaumont
Douaumont is a small commune in northeastern France best known for its World War I battlefield sites near Verdun, including major memorials and military cemeteries.
-
E.
Gerland
Gerland is a district in the 7th arrondissement of Lyon, France, known for its former stadium, biotechnology and research centers, and mixed residential-industrial character.
- 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_69ca8318231881908fd1bc1c4d45d286 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe49064f881909391d565b97e9886 |
completed | March 31, 2026, 3:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce1dea01c481909496ebfca4e9916e |
completed | April 2, 2026, 7:42 a.m. |
Created at: March 30, 2026, 6:10 p.m.