Triple
T7254445
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Presidency of Costa Rica |
E157682
|
entity |
| Predicate | numberOfVicePresidents |
P42776
|
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: [Presidency of Costa Rica, numberOfVicePresidents, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfVicePresidents Context triple: [Presidency of Costa Rica, numberOfVicePresidents, 2]
-
A.
vicePresidentNumber
chosen
Indicates the ordinal position or numerical designation of an individual serving in the role of vice president within a given organization or context.
-
B.
numberOfPresidents
Indicates the total count of individuals who have held the position of president for a given entity or within a specified context.
-
C.
firstVicePresidentialOccupant
Indicates that the subject is the very first individual to hold the office of vice president for the specified entity or position.
-
D.
succeededAsVicePresidentBy
Indicates that one individual ceased serving as vice president and was followed in that office by another specific individual.
-
E.
numberOfCabinetMembers
Indicates the total count of cabinet members associated with a given government, administration, or leader.
- 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_69c6882d81d4819085f7ff862951ee4f |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea9f55b4819081a43e7a01eda154 |
completed | March 27, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69c6e7666ffc81908bf643d8257e6337 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:56 p.m.