Triple
T31120486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vermont congressional delegation |
E793207
|
entity |
| Predicate | senateSeatClass |
P172950
|
FINISHED |
| Object | Class 1 Senate seat from Vermont |
—
|
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: Class 1 Senate seat from Vermont | Statement: [Vermont congressional delegation, senateSeatClass, Class 1 Senate seat from Vermont]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: senateSeatClass Context triple: [Vermont congressional delegation, senateSeatClass, Class 1 Senate seat from Vermont]
-
A.
isPartOfSenateClassSystem
Indicates that an entity belongs to or is categorized within a specific class or grouping of the Senate class system.
-
B.
numberOfSeatsInSenate
Indicates the total count of seats allocated in a given senate.
-
C.
EFFSeats
Indicates a relationship where a person or entity holds or occupies a seat or position within an organization, body, or context.
-
D.
hasSeatingClassification
Indicates that an entity is assigned a specific type or category of seating arrangement or capacity.
-
E.
seatOfCouncil
Indicates that a location serves as the official meeting place or headquarters of a council.
- 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_69f224d0a7688190af3fe3e6e26d01ed |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6b2d9aad88190a445f8f591cb19fc |
completed | May 3, 2026, 2:28 a.m. |
| PD | Predicate disambiguation | batch_69f6b14faf608190a25b977c0740729c |
completed | May 3, 2026, 2:22 a.m. |
| PDg | Predicate description generation | batch_69f6b21da77081908c5c015c4606d344 |
completed | May 3, 2026, 2:25 a.m. |
Created at: April 29, 2026, 9:04 p.m.