Triple
T35648964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Château de Ham, Picardy, Kingdom of France |
E1030085
|
entity |
| Predicate | departmentNow |
P33406
|
FINISHED |
| Object | Somme department |
—
|
NE NERFINISHED |
How this triple was built (2 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: Somme department | Statement: [Château de Ham, Picardy, Kingdom of France, departmentNow, Somme department]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: departmentNow Context triple: [Château de Ham, Picardy, Kingdom of France, departmentNow, Somme department]
-
A.
department
Indicates that one entity functions as an organizational unit or division within another, typically larger, entity.
-
B.
departmentNumber
Indicates the specific numeric code assigned to identify a particular department within an organization or system.
-
C.
presentDayDepartment
chosen
Indicates that an entity is currently administered or located within a specific modern-day department (administrative division).
-
D.
laterDepartment
Indicates that one department occurs or is considered after another in a defined ordering or sequence.
-
E.
motherDepartment
Indicates that one department is the parent or higher-level organizational unit of another department.
- F. None of above.
Provenance (3 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_69f76e0938088190a8f199631e97dec3 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79f7340e4819092a1a47f7028e63f |
completed | May 3, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69f79e4d885881908a3612e2e75cf84f |
completed | May 3, 2026, 7:13 p.m. |
Created at: May 3, 2026, 4:05 p.m.