Triple
T20092362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacques Mornard |
E496302
|
entity |
| Predicate | relationshipCoverStory |
P138683
|
FINISHED |
| Object | Belgian businessman |
—
|
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: Belgian businessman | Statement: [Jacques Mornard, relationshipCoverStory, Belgian businessman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipCoverStory Context triple: [Jacques Mornard, relationshipCoverStory, Belgian businessman]
-
A.
relationshipStatusInStory
Indicates the type or state of the relationship between entities as it exists within the context of a specific story or narrative.
-
B.
relationshipContext
Indicates the situational or social setting in which a relationship between entities exists or occurs.
-
C.
associatedWithPersonInStory
Indicates that one entity has a connection or involvement with a specific person within the context of a story.
-
D.
relationshipFocus
Indicates a relationship where particular attention, priority, or emphasis is placed on the connection between two or more entities.
-
E.
relationshipScope
Indicates the contextual boundaries or extent within which a particular relationship between entities is defined or considered valid.
- 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_69da626eee3881909f3454986d4a6511 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66668db8881908c43b1deef9af1d3 |
completed | April 20, 2026, 5:46 p.m. |
| PD | Predicate disambiguation | batch_69e54cf369b88190931532420517dac7 |
completed | April 19, 2026, 9:45 p.m. |
| PDg | Predicate description generation | batch_69e54fc20888819083c9118a09d0d2dc |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 11, 2026, 11:22 p.m.