Triple
T16036816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | arrondissement of Péronne |
E388988
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Rosières-en-Santerre
Rosières-en-Santerre is a commune in the Somme department of northern France, situated in the historical region of Picardy.
|
E1190702
|
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: Rosières-en-Santerre | Statement: [arrondissement of Péronne, contains, Rosières-en-Santerre]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rosières-en-Santerre Context triple: [arrondissement of Péronne, contains, Rosières-en-Santerre]
-
A.
Santenay
Santenay is a wine-producing village in Burgundy, France, known for its predominantly red wines made from Pinot Noir and its location at the southern end of the Côte de Beaune.
-
B.
Rosières
Rosières is a village and district within the municipality of Rixensart in Walloon Brabant, Belgium.
-
C.
Rosières
Rosières is a locality within the municipality of Vaux-sur-Sûre in the Walloon region of Belgium.
-
D.
Orsières
Orsières is a Swiss municipality in the canton of Valais, known as a gateway to alpine passes and popular mountain tourism areas.
-
E.
Eygalières
Eygalières is a picturesque Provençal village in southern France, known for its stone houses, historic charm, and scenic setting amid the Alpilles hills.
- 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: Rosières-en-Santerre Triple: [arrondissement of Péronne, contains, Rosières-en-Santerre]
Generated description
Rosières-en-Santerre is a commune in the Somme department of northern France, situated in the historical region of Picardy.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rosières-en-Santerre Target entity description: Rosières-en-Santerre is a commune in the Somme department of northern France, situated in the historical region of Picardy.
-
A.
Santenay
Santenay is a wine-producing village in Burgundy, France, known for its predominantly red wines made from Pinot Noir and its location at the southern end of the Côte de Beaune.
-
B.
Rosières
Rosières is a village and district within the municipality of Rixensart in Walloon Brabant, Belgium.
-
C.
Rosières
Rosières is a locality within the municipality of Vaux-sur-Sûre in the Walloon region of Belgium.
-
D.
Orsières
Orsières is a Swiss municipality in the canton of Valais, known as a gateway to alpine passes and popular mountain tourism areas.
-
E.
Eygalières
Eygalières is a picturesque Provençal village in southern France, known for its stone houses, historic charm, and scenic setting amid the Alpilles hills.
- 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_69d86dada3808190825d5f80d72fbe88 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1833ca66881909475fac23e6fbf86 |
completed | April 17, 2026, 12:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffdbd3a1248190ad055892cebde5f0 |
completed | May 10, 2026, 1:13 a.m. |
| NEDg | Description generation | batch_69ffdc5fd30c8190aaf66482f24285b4 |
completed | May 10, 2026, 1:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffdd0392e08190af42a0cdc5dd4c1f |
completed | May 10, 2026, 1:18 a.m. |
Created at: April 10, 2026, 4:56 a.m.