Triple
T1841249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 4th arrondissement of Paris |
E41180
|
entity |
| Predicate | administrativeNumber |
P34024
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [4th arrondissement of Paris, administrativeNumber, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: administrativeNumber Context triple: [4th arrondissement of Paris, administrativeNumber, 4]
-
A.
administrativeFeature
Indicates that one entity serves as an administrative or governance-related feature, function, or attribute associated with another entity.
-
B.
administeredBy
Indicates that an action, service, or process is carried out, managed, or overseen by a specified agent or authority.
-
C.
officeNumber
Indicates the specific room or suite number assigned to an office within a building or complex.
-
D.
SSNumber
Indicates that an entity has a specific Social Security Number assigned to it.
-
E.
administeredAs
Indicates that one entity is given or applied to another entity as a treatment, dose, or intervention.
- 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_69a88647f9388190909bc36e795bdaec |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb32d35508190bf1c487dffbecaf0 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafdb0d2c8190a67f584e67979fa3 |
completed | March 7, 2026, 4:55 a.m. |
| PDg | Predicate description generation | batch_69abb32a8d548190a231c7c2ce276a5e |
completed | March 7, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:33 p.m.