Triple
T12657143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First Lady of France |
E302313
|
entity |
| Predicate | oftenLeads |
P18658
|
FINISHED |
| Object | social initiatives |
—
|
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: social initiatives | Statement: [First Lady of France, oftenLeads, social initiatives]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenLeads Context triple: [First Lady of France, oftenLeads, social initiatives]
-
A.
helpsLead
Indicates that one entity assists or contributes to another entity’s act of leading or guiding.
-
B.
leadsAstray
Indicates that one entity causes another entity to deviate from a correct, moral, or intended path or course of action.
-
C.
leadsInto
Indicates that one entity serves as an entry or transition point that directly connects or opens into another entity.
-
D.
canLeadTo
chosen
Indicates that one entity, condition, or event has the potential to cause, result in, or bring about another.
-
E.
leads
Indicates having primary responsibility for directing, guiding, or managing another entity or group toward a goal or outcome.
- 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9617b07ec8190b714f04ae6654060 |
completed | April 10, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69d960b78ce8819091f15dd5013e6da5 |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:18 p.m.