Triple
T81236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | President of the United States Senate |
E1630
|
entity |
| Predicate | termCoincidesWith |
P1867
|
FINISHED |
| Object | term of the Vice President of the United States |
—
|
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: term of the Vice President of the United States | Statement: [President of the United States Senate, termCoincidesWith, term of the Vice President of the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: termCoincidesWith Context triple: [President of the United States Senate, termCoincidesWith, term of the Vice President of the United States]
-
A.
overlapsWith
chosen
Indicates that two entities share a common part or region in space, time, or extent, but neither is completely contained within the other.
-
B.
meetsEvery
Indicates that one entity encounters or comes into contact with every member of a specified set of entities.
-
C.
hasTerm
Indicates that an entity includes, is associated with, or is defined by a specific term or condition.
-
D.
coordinatedWith
Indicates that two or more entities have worked together in an organized, cooperative manner toward a shared task, goal, or activity.
-
E.
meetsDuring
Indicates that one entity encounters or comes together with another while a specified event or time interval is in progress.
- 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_69a24c60d19c8190a1b6c105ca59ef5b |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a25053ca208190a371b0d38000c2b9 |
completed | Feb. 28, 2026, 2:17 a.m. |
| PD | Predicate disambiguation | batch_69a24eb2998c819082681da74601d446 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.