Triple
T32470712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Senate seat from Virginia |
E829839
|
entity |
| Predicate | numberOfCurrentIncumbents |
P113810
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [United States Senate seat from Virginia, numberOfCurrentIncumbents, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCurrentIncumbents Context triple: [United States Senate seat from Virginia, numberOfCurrentIncumbents, 2]
-
A.
numberOfIncumbents
chosen
Indicates the count of entities currently holding a particular position, role, or status at a given time.
-
B.
hasMultipleIncumbents
Indicates that a given position, role, or office is simultaneously held by more than one incumbent.
-
C.
firstOfficeHoldersCount
Indicates the number of individuals who initially held a particular office or position.
-
D.
officeHoldersNumber
Indicates the number of individuals who hold a particular office or position.
-
E.
numberOfGovernmentSenators
Indicates the total count of senators who are members of the government (ruling party or coalition) associated with a given entity or context.
- 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_69f3491ee87c81908cbf5890079c2af6 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a01bb9c33cc8190a95ba124d97edf99 |
completed | May 11, 2026, 11:21 a.m. |
| PD | Predicate disambiguation | batch_6a01bb6772148190a243d1141ad0a237 |
completed | May 11, 2026, 11:20 a.m. |
Created at: May 1, 2026, 12:57 a.m.