Triple
T14208046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madame Valmondé |
E352151
|
entity |
| Predicate | concernFor |
P11116
|
FINISHED |
| Object | well-being of Désirée |
—
|
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: well-being of Désirée | Statement: [Madame Valmondé, concernFor, well-being of Désirée]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: concernFor Context triple: [Madame Valmondé, concernFor, well-being of Désirée]
-
A.
concern
chosen
Indicates that one entity is about, relates to, or is of interest or importance to another entity.
-
B.
concernedSee
Indicates that one entity looks at or observes another with a sense of worry, care, or concern.
-
C.
strategicConcernFor
Indicates a relationship where one entity considers another entity’s situation, actions, or outcomes important for its own long-term goals, risks, or strategic interests.
-
D.
targetConcern
Indicates that something is the specific issue, problem, or subject that is the focus of attention, action, or consideration.
-
E.
concernsFeature
Indicates that something is about, relates to, or involves a particular feature.
- F. None of above.
Provenance (3 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_69d8278a06e481908b5d6af0a8afe737 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61f84f288190877116330bd54393 |
completed | April 14, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69de05bcd7d48190a4848d9320404aa6 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:05 a.m.