Triple
T7771994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aleksander Kwaśniewski |
E179094
|
entity |
| Predicate | numberOfTermInOffice |
P78246
|
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: [Aleksander Kwaśniewski, numberOfTermInOffice, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTermInOffice Context triple: [Aleksander Kwaśniewski, numberOfTermInOffice, 2]
-
A.
termInOffice
Indicates the period during which an individual officially holds a particular office or position.
-
B.
electsTermLength
Indicates the length of time for which an entity is elected to hold a particular position or office.
-
C.
termLength
Indicates the duration or period of time for which an agreement, position, or condition remains in effect.
-
D.
presidentialTerm
Indicates the period of time during which an individual officially serves as president of a country or organization.
-
E.
setsTermOfOfficeFor
Indicates that one entity establishes or defines the duration and conditions of the term of office for another entity.
- F. None of above. chosen
Provenance (4 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_69c69f30602c819082ab52cd4af5c592 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c7045ebae88190a04c8f972795e615 |
completed | March 27, 2026, 10:27 p.m. |
| PD | Predicate disambiguation | batch_69c7016f4ce881909c2e9f610255187b |
completed | March 27, 2026, 10:15 p.m. |
| PDg | Predicate description generation | batch_69c702a78edc819090c3448d33c8c381 |
completed | March 27, 2026, 10:20 p.m. |
Created at: March 27, 2026, 4:11 p.m.