Triple
T20558027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joko Widodo |
E504771
|
entity |
| Predicate | firstElectedAsPresident |
P140554
|
FINISHED |
| Object | 2014 |
—
|
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: 2014 | Statement: [Joko Widodo, firstElectedAsPresident, 2014]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstElectedAsPresident Context triple: [Joko Widodo, firstElectedAsPresident, 2014]
-
A.
firstElectedPresident
Indicates that the subject became the first person ever elected to the office of president of the specified entity or organization.
-
B.
firstElectoralVoteRecipient
Indicates that the subject was the first candidate or option to receive an electoral vote in a given election or electoral context.
-
C.
wasFirstPresidentAfter
Indicates that one entity served as the first president immediately following another specified entity.
-
D.
firstPresidentUnder
Indicates that one entity is the first president to serve under, or within the tenure or authority of, another entity (such as a country, organization, or regime).
-
E.
inauguralWinnerOf
Indicates that one entity is the first-ever winner of a particular event, award, or competition.
- 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_69e0b4b6587c8190aee63dc7cff244ea |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a5df84088190848c7eb35564d8f9 |
completed | April 20, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69e59ff0116c8190a163ff28ed01430a |
completed | April 20, 2026, 3:39 a.m. |
| PDg | Predicate description generation | batch_69e5a6a824748190bbe6192d73f3c613 |
completed | April 20, 2026, 4:08 a.m. |
Created at: April 16, 2026, 11:38 a.m.