Triple
T28772544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris (department) |
E726449
|
entity |
| Predicate | isUniqueDepartmentCoextensiveWithCity |
P165571
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Paris (department), isUniqueDepartmentCoextensiveWithCity, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUniqueDepartmentCoextensiveWithCity Context triple: [Paris (department), isUniqueDepartmentCoextensiveWithCity, true]
-
A.
belongsToDepartmentCapitalRegion
Indicates that an entity is part of, or administratively assigned to, the capital region of a department.
-
B.
refersToDepartmentInRegion
Indicates that an entity is associated with, or makes reference to, a specific department located within a particular region.
-
C.
isSingleDistrictFor
Indicates that one district uniquely and exclusively serves or applies to a given entity, with no other districts sharing that role.
-
D.
capitalOfDepartment
Indicates that a city or town serves as the administrative capital of a specified department (an administrative division).
-
E.
cityDepartment
Indicates that one entity is a department that operates within, or is administratively part of, a particular city.
- 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_69f03199997c8190b6ae43fb19312443 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f6596b210481908af6cd555748f75b |
completed | May 2, 2026, 8:07 p.m. |
| PD | Predicate disambiguation | batch_69f65760fd3081908ffe014a5e2bf069 |
completed | May 2, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f658ebeca4819096beb3f98f73fe31 |
completed | May 2, 2026, 8:05 p.m. |
Created at: April 28, 2026, 6:16 a.m.