Triple
T25291993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mailjet |
E634110
|
entity |
| Predicate | hasCTO |
P158356
|
FINISHED |
| Object | Markus Sattler |
—
|
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: Markus Sattler | Statement: [Mailjet, hasCTO, Markus Sattler]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCTO Context triple: [Mailjet, hasCTO, Markus Sattler]
-
A.
hasCP
Indicates that an entity possesses, is associated with, or is characterized by a specific CP (such as a control point, contact person, or configuration parameter), depending on the domain context.
-
B.
hasCcf
Indicates that one entity possesses, is associated with, or is characterized by a specific CCF (the exact nature of which is defined elsewhere in the model or ontology).
-
C.
hasButler
Indicates that one entity employs or is served by another entity in the role of a butler.
-
D.
hasCatalyst
Indicates that a process, reaction, or transformation occurs with the involvement of a specific catalyst that facilitates or accelerates it.
-
E.
hasCEP
Indicates that an entity is associated with a specific postal code (CEP), typically identifying its mailing or geographic location.
- 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_69e75a9503d48190b80a005c6af0cb50 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f48fce2f548190a412ae2b6c7d73f6 |
completed | May 1, 2026, 11:34 a.m. |
| PD | Predicate disambiguation | batch_69f45d06d0388190b36ecde92013624a |
completed | May 1, 2026, 7:57 a.m. |
| PDg | Predicate description generation | batch_69f465699c9c8190ac7b4b32b782550c |
completed | May 1, 2026, 8:33 a.m. |
Created at: April 21, 2026, 1:22 p.m.