Triple
T7913843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louise Bénédicte de Bourbon |
E183765
|
entity |
| Predicate | socialNetwork |
P44645
|
FINISHED |
| Object | French nobility |
—
|
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: French nobility | Statement: [Louise Bénédicte de Bourbon, socialNetwork, French nobility]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: socialNetwork Context triple: [Louise Bénédicte de Bourbon, socialNetwork, French nobility]
-
A.
socialSystem
Indicates a relationship where entities are organized into a structured set of social roles, norms, and interactions that govern their collective behavior.
-
B.
socialFeature
Indicates that one entity provides or participates in a social interaction capability or function involving other entities.
-
C.
socialSphere
chosen
Indicates the social environment or network within which an entity regularly interacts or maintains relationships.
-
D.
socialBase
Indicates a foundational social relationship or structure that underlies or supports interactions between entities.
-
E.
socialComposition
Indicates the makeup or distribution of different social groups or categories within a population or community.
- 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_69ca828dec0c81908b8f55a4dbbb53ff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a748f4c8190bcd868de2fcf0b3a |
completed | March 31, 2026, 3:07 a.m. |
| PD | Predicate disambiguation | batch_69cae92f9498819085277879e59aa072 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:04 p.m.