Triple
T30376610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blanche Richel |
E772706
|
entity |
| Predicate | spouseOfPositionHeldByHusband |
P26554
|
FINISHED |
| Object | President of France |
—
|
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: President of France | Statement: [Blanche Richel, spouseOfPositionHeldByHusband, President of France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseOfPositionHeldByHusband Context triple: [Blanche Richel, spouseOfPositionHeldByHusband, President of France]
-
A.
spouseOffice
chosen
Indicates that one entity holds an office or position that is associated with, or held by, the spouse of another entity.
-
B.
spouseDiplomaticRole
Indicates that one person is the spouse of another person who holds or held a diplomatic position or role.
-
C.
spouseLaterOffice
Indicates that one person’s spouse held a particular office or position at a later time than the person in question.
-
D.
spouseOfHead
Indicates that one person is the married partner of the individual who holds the position of head (e.g., head of a household, organization, or state).
-
E.
spouseOfRole
Indicates that one role is the spouse (husband, wife, or equivalent marital partner) of another role.
- 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_69f2248e3444819081b05712dc6873de |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fce7671f108190bf3ebf54339068b5 |
completed | May 7, 2026, 7:26 p.m. |
| PD | Predicate disambiguation | batch_69fce5b5a84c81908ac1b5b9f08d48d0 |
completed | May 7, 2026, 7:19 p.m. |
Created at: April 29, 2026, 8 p.m.