Triple
T4042405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marmande |
E83980
|
entity |
| Predicate | departmentalRole |
P47000
|
FINISHED |
| Object | seat of the arrondissement of Marmande |
—
|
LITERAL FINISHED |
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: seat of the arrondissement of Marmande | Statement: [Marmande, departmentalRole, seat of the arrondissement of Marmande]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: departmentalRole Context triple: [Marmande, departmentalRole, seat of the arrondissement of Marmande]
-
A.
departmentType
Indicates the classification or category of a department, specifying what kind of department it is.
-
B.
hasDepartmentSeatRole
chosen
Indicates that an entity holds a specific role or position associated with a seat in a particular department.
-
C.
roleInCommandStructure
Indicates that one entity holds a specific position or function within the hierarchical command structure of another entity or organization.
-
D.
typeOfRole
Indicates that one entity specifies the kind or category of role that another entity holds or performs.
-
E.
officeItAbbreviatesRole
Indicates that an office title or designation serves as an abbreviation for a particular role or position.
- 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_69aed92f7cf0819098e0539bdcc3767f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb5b65c08190ba3f340ed18737f8 |
completed | March 9, 2026, 4:54 p.m. |
| PD | Predicate disambiguation | batch_69aef900386481909d04555a9ec9b0e3 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:37 p.m.