Triple
T1879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franklin D. Roosevelt |
E34
|
entity |
| Predicate | firstInOfficeTo |
P291
|
FINISHED |
| Object | be elected to four terms as U.S. president |
—
|
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: be elected to four terms as U.S. president | Statement: [Franklin D. Roosevelt, firstInOfficeTo, be elected to four terms as U.S. president]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstInOfficeTo Context triple: [Franklin D. Roosevelt, firstInOfficeTo, be elected to four terms as U.S. president]
-
A.
hasPresident
Indicates that an entity holds the position or role of president for another entity.
-
B.
appointedBy
Indicates that one entity has been formally selected or assigned to a position, role, or office by another entity.
-
C.
termCountAsPresident
Indicates the number of terms an individual has served in the role of president.
-
D.
vicePresident
Indicates that one entity holds the role of second-in-command or deputy leader to another entity within an organizational or governmental hierarchy.
-
E.
firstAwarded
Indicates the time or occasion when an award, honor, or recognition was given for the very first time.
- 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_69a22cde80848190b62c5f556b4d62ba |
completed | Feb. 27, 2026, 11:46 p.m. |
| NER | Named-entity recognition | batch_69a23344daf8819083118bbac5f46568 |
completed | Feb. 28, 2026, 12:13 a.m. |
| PD | Predicate disambiguation | batch_69a232e52e7c81909c072703e28e8c61 |
completed | Feb. 28, 2026, 12:12 a.m. |
| PDg | Predicate description generation | batch_69a233443224819097b91b150fdfbd1a |
completed | Feb. 28, 2026, 12:13 a.m. |
Created at: Feb. 27, 2026, 11:48 p.m.