Triple
T18912987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kumar Sangakkara |
E462650
|
entity |
| Predicate | mccPresidencyNote |
P13645
|
FINISHED |
| Object | first non-British president of MCC |
—
|
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: first non-British president of MCC | Statement: [Kumar Sangakkara, mccPresidencyNote, first non-British president of MCC]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mccPresidencyNote Context triple: [Kumar Sangakkara, mccPresidencyNote, first non-British president of MCC]
-
A.
officeAssumedAsPresidentFollowing
Indicates that one entity assumed the office of president immediately after another entity, in a direct succession.
-
B.
presidentialView
Indicates that an entity holds an official or characteristic perspective, stance, or outlook associated with a presidency or presidential role.
-
C.
hasPresident
Indicates that an entity holds the position or role of president for another entity.
-
D.
presidency
chosen
Indicates that an entity holds or relates to the office, role, or term of serving as president over a state, organization, or institution.
-
E.
presidencyNature
Indicates the type or character of a presidency, such as its style, structure, or defining institutional features, in relation to a given office or term.
- 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_69d8dcfdbbb881909964fa5a75bd0b48 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c624516c81909e6bf04707d3c71c |
completed | April 20, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69e4a2e9e6488190ba8df92c8058ed88 |
completed | April 19, 2026, 9:39 a.m. |
Created at: April 10, 2026, 11:58 a.m.