Triple
T11977048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles Mangin |
E285065
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Sarrebourg |
E294134
|
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: Sarrebourg | Statement: [Charles Mangin, placeOfBirth, Sarrebourg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sarrebourg Context triple: [Charles Mangin, placeOfBirth, Sarrebourg]
-
A.
Sarrebourg
chosen
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.
-
B.
Sarreguemines
Sarreguemines is a town in northeastern France near the German border, historically known for its ceramics and faience production.
-
C.
Berg-sur-Moselle
Berg-sur-Moselle is a small French commune in the Moselle department of northeastern France, near the border with Luxembourg.
-
D.
Obernai
Obernai is a historic Alsatian town in northeastern France known for its well-preserved medieval architecture, wine production, and picturesque setting along the Alsace Wine Route.
-
E.
Bettembourg
Bettembourg is a town in southern Luxembourg known as a key railway junction and border-crossing point on the national rail network.
- 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903926690819090e7ce982f103457 |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f70a114ccc81909bc428c40c01a461 |
completed | May 3, 2026, 8:40 a.m. |
Created at: April 8, 2026, 9:46 p.m.