Triple
T8095980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tim Kaine |
E188985
|
entity |
| Predicate | firstElectedToSenate |
P80448
|
FINISHED |
| Object | 2012 |
—
|
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: 2012 | Statement: [Tim Kaine, firstElectedToSenate, 2012]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstElectedToSenate Context triple: [Tim Kaine, firstElectedToSenate, 2012]
-
A.
precededInSenateBy
Indicates that one officeholder directly held a given Senate seat before another officeholder, in terms of succession to that seat.
-
B.
representedInSenate
Indicates that an entity serves as a representative for another entity within a senate or upper legislative chamber.
-
C.
firstRepresentationInCongress
Indicates that an entity marks the initial time or instance another entity is represented in a specific session or body of Congress.
-
D.
senateMembership
Indicates that an entity holds or has held a position as a member of a senate.
-
E.
succeededInOfficeAsSenatorFromNewYorkBy
Indicates that one individual was succeeded in the role of Senator from New York by another individual.
- 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_69ca82b886d88190a9cba0d5a4a27521 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4291f1d4819098985ac2b20b6c75 |
completed | March 31, 2026, 3:42 a.m. |
| PD | Predicate disambiguation | batch_69cb04a14cd88190a79ed26cbeec1c33 |
completed | March 30, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69cb14be17208190bb51c3dfcb613f20 |
completed | March 31, 2026, 12:26 a.m. |
Created at: March 30, 2026, 5:30 p.m.