Triple
T16036855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | canton of Ham |
E388989
|
entity |
| Predicate | containsAdministrativeTerritory |
P15909
|
FINISHED |
| Object |
Matigny
Matigny is a small commune in the Somme department of northern France, situated within the canton of Ham.
|
E1197182
|
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: Matigny | Statement: [canton of Ham, containsAdministrativeTerritory, Matigny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matigny Context triple: [canton of Ham, containsAdministrativeTerritory, Matigny]
-
A.
Berlencourt
Berlencourt is a small commune in northern France, located within the Nord department in the Hauts-de-France region.
-
B.
Jumièges
Jumièges is a commune in northern France best known for the ruins of its historic Benedictine abbey, Jumièges Abbey, a major example of Norman Romanesque architecture.
-
C.
Watigny
Watigny is a commune in northern France, likely situated in a hilly or elevated area that includes Mont Watigny.
-
D.
Comines
Comines is a town situated along the Lys River in the historic Flanders region on the border between France and Belgium.
-
E.
Blanchimont
Blanchimont is a famously fast, sweeping left-hand corner at Belgium’s Circuit de Spa-Francorchamps, known for its high-speed challenge and minimal runoff.
- 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: Matigny Triple: [canton of Ham, containsAdministrativeTerritory, Matigny]
Generated description
Matigny is a small commune in the Somme department of northern France, situated within the canton of Ham.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Matigny Target entity description: Matigny is a small commune in the Somme department of northern France, situated within the canton of Ham.
-
A.
Berlencourt
Berlencourt is a small commune in northern France, located within the Nord department in the Hauts-de-France region.
-
B.
Jumièges
Jumièges is a commune in northern France best known for the ruins of its historic Benedictine abbey, Jumièges Abbey, a major example of Norman Romanesque architecture.
-
C.
Watigny
Watigny is a commune in northern France, likely situated in a hilly or elevated area that includes Mont Watigny.
-
D.
Comines
Comines is a town situated along the Lys River in the historic Flanders region on the border between France and Belgium.
-
E.
Blanchimont
Blanchimont is a famously fast, sweeping left-hand corner at Belgium’s Circuit de Spa-Francorchamps, known for its high-speed challenge and minimal runoff.
- 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_69fff796fafc8190b6cfb2d8ea502eef |
completed | May 10, 2026, 3:12 a.m. |
| NEDg | Description generation | batch_69fff8ab1ad881909868dc4009ebb25a |
completed | May 10, 2026, 3:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fff93cc140819087167f99efa4dead |
completed | May 10, 2026, 3:19 a.m. |
Created at: April 10, 2026, 4:56 a.m.