Triple
T2044660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles-François Lebrun |
E45422
|
entity |
| Predicate | placeOfDeath |
P21
|
FINISHED |
| Object |
Sainte-Mesme
Sainte-Mesme is a small commune in the Île-de-France region of north-central France.
|
E230709
|
NE FINISHED |
How this triple was built (4 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: Sainte-Mesme | Statement: [Charles-François Lebrun, placeOfDeath, Sainte-Mesme]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sainte-Mesme Context triple: [Charles-François Lebrun, placeOfDeath, Sainte-Mesme]
-
A.
Béthune
Béthune is a historic town in northern France known for its medieval belfry and role as a regional center in the former County of Artois.
-
B.
Montmédy
Montmédy is a fortified town in northeastern France near the Luxembourg and Belgian borders, historically significant as the intended royal refuge during the failed Flight to Varennes in 1791.
-
C.
Gouy, Aisne
Gouy is a commune in the Aisne department of northern France, notable as the area where the Scheldt River has its source.
-
D.
Maubeuge
Maubeuge is a fortified industrial town in northern France near the Belgian border, historically significant for its strategic military position.
-
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. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Sainte-Mesme Triple: [Charles-François Lebrun, placeOfDeath, Sainte-Mesme]
Generated description
Sainte-Mesme is a small commune in the Île-de-France region of north-central France.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sainte-Mesme Target entity description: Sainte-Mesme is a small commune in the Île-de-France region of north-central France.
-
A.
Béthune
Béthune is a historic town in northern France known for its medieval belfry and role as a regional center in the former County of Artois.
-
B.
Montmédy
Montmédy is a fortified town in northeastern France near the Luxembourg and Belgian borders, historically significant as the intended royal refuge during the failed Flight to Varennes in 1791.
-
C.
Gouy, Aisne
Gouy is a commune in the Aisne department of northern France, notable as the area where the Scheldt River has its source.
-
D.
Maubeuge
Maubeuge is a fortified industrial town in northern France near the Belgian border, historically significant for its strategic military position.
-
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. chosen
Provenance (5 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_69a8891948208190ab7898da21824c77 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb97153b08190b91d82f4117982be |
completed | March 7, 2026, 5:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae271399a08190946b315f439b9b2f |
completed | March 9, 2026, 1:49 a.m. |
| NEDg | Description generation | batch_69ae2847a7e0819092026253e036bd1c |
completed | March 9, 2026, 1:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae28ce87c8819097e0b5dab045d9a1 |
completed | March 9, 2026, 1:56 a.m. |
Created at: March 4, 2026, 7:39 p.m.