Triple
T16469920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canton of Moreuil |
E400032
|
entity |
| Predicate | containsCommune |
P15149
|
FINISHED |
| Object |
Fouquescourt
Fouquescourt is a small rural commune in northern France’s Somme department, characterized by its agricultural landscape and traditional Picard village setting.
|
E1216546
|
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: Fouquescourt | Statement: [Canton of Moreuil, containsCommune, Fouquescourt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fouquescourt Context triple: [Canton of Moreuil, containsCommune, Fouquescourt]
-
A.
Blignicourt
Blignicourt is a small commune in the Aube department of north-central France.
-
B.
Juvancourt
Juvancourt is a small commune in the Aube department in north-central France.
-
C.
Bois-de-Villers
Bois-de-Villers is a village in the municipality of Jalhay in the Walloon region of Belgium, known for its rural setting in the Ardennes.
-
D.
Beaucourt
Beaucourt is a small French commune located in the northeastern region of Bourgogne-Franche-Comté near the Swiss border.
-
E.
Morlaincourt
Morlaincourt is a small commune in northeastern France, likely known locally for its rural character and proximity to the Yonne river’s headwaters.
- 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: Fouquescourt Triple: [Canton of Moreuil, containsCommune, Fouquescourt]
Generated description
Fouquescourt is a small rural commune in northern France’s Somme department, characterized by its agricultural landscape and traditional Picard village setting.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Fouquescourt Target entity description: Fouquescourt is a small rural commune in northern France’s Somme department, characterized by its agricultural landscape and traditional Picard village setting.
-
A.
Blignicourt
Blignicourt is a small commune in the Aube department of north-central France.
-
B.
Juvancourt
Juvancourt is a small commune in the Aube department in north-central France.
-
C.
Bois-de-Villers
Bois-de-Villers is a village in the municipality of Jalhay in the Walloon region of Belgium, known for its rural setting in the Ardennes.
-
D.
Beaucourt
Beaucourt is a small French commune located in the northeastern region of Bourgogne-Franche-Comté near the Swiss border.
-
E.
Morlaincourt
Morlaincourt is a small commune in northeastern France, likely known locally for its rural character and proximity to the Yonne river’s headwaters.
- 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_69d87f2dac988190b74d6e185fa88ba4 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32dcfed6c8190b8dbe4b65b0ab817 |
completed | April 18, 2026, 7:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00581c24508190b4888357828fed80 |
completed | May 10, 2026, 10:04 a.m. |
| NEDg | Description generation | batch_6a00592562708190ae88f24fb34c7a02 |
completed | May 10, 2026, 10:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a005a17fd648190b2c6843f47a9ee2c |
completed | May 10, 2026, 10:12 a.m. |
Created at: April 10, 2026, 5:11 a.m.