Triple
T3135789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pierre Bérégovoy |
E65525
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object |
Seine-Inférieure
Seine-Inférieure was a former department in northern France, largely corresponding to today’s Seine-Maritime in the Normandy region.
|
E444461
|
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: Seine-Inférieure | Statement: [Pierre Bérégovoy, placeOfBirth, Seine-Inférieure]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seine-Inférieure Context triple: [Pierre Bérégovoy, placeOfBirth, Seine-Inférieure]
-
A.
Vallée de la Marne
Vallée de la Marne is a key subregion of France’s Champagne wine area, known for its vineyards along the Marne River and its significant production of Pinot Meunier–based sparkling wines.
-
B.
Source-Seine
Source-Seine is the small commune in eastern France where the River Seine originates.
-
C.
Aisne
Aisne is a river in northeastern France that flows through the Champagne and Picardy regions before joining the Oise River.
-
D.
Aisne
Aisne is a department in northern France known for its historic towns, World War I battlefields, and rural landscapes.
-
E.
Val-d'Oise
Val-d'Oise is a department in northern France that forms part of the Paris metropolitan region and includes both suburban areas and rural landscapes.
- 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: Seine-Inférieure Triple: [Pierre Bérégovoy, placeOfBirth, Seine-Inférieure]
Generated description
Seine-Inférieure was a former department in northern France, largely corresponding to today’s Seine-Maritime in the Normandy region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Seine-Inférieure Target entity description: Seine-Inférieure was a former department in northern France, largely corresponding to today’s Seine-Maritime in the Normandy region.
-
A.
Vallée de la Marne
Vallée de la Marne is a key subregion of France’s Champagne wine area, known for its vineyards along the Marne River and its significant production of Pinot Meunier–based sparkling wines.
-
B.
Source-Seine
Source-Seine is the small commune in eastern France where the River Seine originates.
-
C.
Aisne
Aisne is a river in northeastern France that flows through the Champagne and Picardy regions before joining the Oise River.
-
D.
Aisne
Aisne is a department in northern France known for its historic towns, World War I battlefields, and rural landscapes.
-
E.
Val-d'Oise
Val-d'Oise is a department in northern France that forms part of the Paris metropolitan region and includes both suburban areas and rural landscapes.
- 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_69ad8581c25c8190b0d85ba9b9baa531 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada5637de0819089393429c4017298 |
completed | March 8, 2026, 4:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b65efe2ab881909bc709f369a75b6f |
completed | March 15, 2026, 7:25 a.m. |
| NEDg | Description generation | batch_69b66008494c81908205772ba3cf29be |
completed | March 15, 2026, 7:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b66069b8708190b3351c68484dc034 |
completed | March 15, 2026, 7:31 a.m. |
Created at: March 8, 2026, 3:05 p.m.