Triple
T5242860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michel Ney |
E118385
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object | Saarlouis, Kingdom of France |
E339974
|
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: Saarlouis, Kingdom of France | Statement: [Michel Ney, birthPlace, Saarlouis, Kingdom of France]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saarlouis, Kingdom of France Context triple: [Michel Ney, birthPlace, Saarlouis, Kingdom of France]
-
A.
Saarlouis
chosen
Saarlouis is a town in the German state of Saarland, known historically as a fortified city founded by Louis XIV of France near the French border.
-
B.
Sarrebourg
Sarrebourg is a small historic town in northeastern France known for its cultural heritage and location in the Moselle department of the Grand Est region.
-
C.
Saarbrücken
Saarbrücken is a German city on the Saar River known as an industrial, cultural, and educational center near the French border.
-
D.
Haguenau
Haguenau is a historic town in northeastern France’s Alsace region, known for its medieval heritage, cultural traditions, and role as a local economic center.
-
E.
Thionville
Thionville is a town in northeastern France near the Luxembourg border, known historically as a strategic industrial and military center in the Moselle region.
- 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_69bd4468aacc8190a8196f71855cdf4f |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7b4c6fa8819099442b1b110e51fb |
completed | March 20, 2026, 4:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69befe65e3048190899a6316dc4c89eb |
completed | March 21, 2026, 8:24 p.m. |
Created at: March 20, 2026, 1:49 p.m.