Triple
T58525
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chief Justice of the United States |
E1158
|
entity |
| Predicate | ceremonialRole |
P3343
|
FINISHED |
| Object | administers the presidential oath of office |
—
|
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: administers the presidential oath of office | Statement: [Chief Justice of the United States, ceremonialRole, administers the presidential oath of office]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ceremonialRole Context triple: [Chief Justice of the United States, ceremonialRole, administers the presidential oath of office]
-
A.
monarchRole
Indicates that an entity holds or is assigned the role, office, or position of a monarch in relation to a state or domain.
-
B.
honorificRank
Indicates that one entity holds a formal title or honorific status in relation to another entity.
-
C.
servedAs
Indicates that one entity held and performed the role, position, or function associated with another entity for some period of time.
-
D.
religiousTitle
Indicates that one entity holds or is referred to by a specific religious rank, honorific, or clerical title in relation to another entity.
-
E.
ceremonyLocation
Indicates the place where a ceremony is held or takes place.
- 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_69a248adc5b48190aa8db9fb092fb28a |
completed | Feb. 28, 2026, 1:45 a.m. |
| NER | Named-entity recognition | batch_69a24c9057348190aa6692eeeae19569 |
completed | Feb. 28, 2026, 2:01 a.m. |
| PD | Predicate disambiguation | batch_69a24ac7547c81909bb68f327cdb9158 |
completed | Feb. 28, 2026, 1:54 a.m. |
| PDg | Predicate description generation | batch_69a24c8fa20c8190aacc38e53d1f654c |
completed | Feb. 28, 2026, 2:01 a.m. |
Created at: Feb. 28, 2026, 1:50 a.m.