Triple
T215686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allier department |
E4815
|
entity |
| Predicate | departmentNumber |
P9698
|
FINISHED |
| Object | 03 |
—
|
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: 03 | Statement: [Allier department, departmentNumber, 03]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: departmentNumber Context triple: [Allier department, departmentNumber, 03]
-
A.
department
Indicates that one entity functions as an organizational unit or division within another, typically larger, entity.
-
B.
departmentType
Indicates the classification or category of a department, specifying what kind of department it is.
-
C.
officeNumber
Indicates the specific room or suite number assigned to an office within a building or complex.
-
D.
civilianLeaderDepartment
Indicates that a person serves as the civilian head or chief official of a specified government department or ministry.
-
E.
notTiedToSingleDepartment
Indicates that the entity is not exclusively associated with or restricted to a single department.
- F. None of above. chosen
Provenance (4 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_69a2575cb1dc8190a01ad332426dc339 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25dcd2b208190855d5d8d70a3acfc |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b52190481908f299d26122bafd2 |
completed | Feb. 28, 2026, 3:04 a.m. |
| PDg | Predicate description generation | batch_69a25dcba5148190ab80fd14c7cf4bb4 |
completed | Feb. 28, 2026, 3:15 a.m. |
Created at: Feb. 28, 2026, 2:52 a.m.