Triple
T810956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Micheline Calmy-Rey |
E17542
|
entity |
| Predicate | numberOfTermsAsPresidentOfTheConfederation |
P152
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Micheline Calmy-Rey, numberOfTermsAsPresidentOfTheConfederation, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTermsAsPresidentOfTheConfederation Context triple: [Micheline Calmy-Rey, numberOfTermsAsPresidentOfTheConfederation, 2]
-
A.
presidentialTerm
Indicates the period of time during which an individual officially serves as president of a country or organization.
-
B.
termCountAsPresident
chosen
Indicates the number of terms an individual has served in the role of president.
-
C.
numberOfPresidents
Indicates the total count of individuals who have held the position of president for a given entity or within a specified context.
-
D.
numberOfColoniesRepresented
Indicates the count of distinct colonies that are represented or involved in relation to a given entity or context.
-
E.
confederation
Indicates a formal union or alliance between multiple entities that retain their individual autonomy while cooperating under a shared framework or agreement.
- 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_69a4937ae8a08190b5084a03d532b30e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ab4c7418819085cb64c6bf5fa70c |
completed | March 1, 2026, 9:10 p.m. |
| PD | Predicate disambiguation | batch_69a4aa73df08819096d0553a4b2509de |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.