Triple
T4888199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Senate |
E109492
|
entity |
| Predicate | hasNumberOfRepresentativesPerState |
P4273
|
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, hasNumberOfRepresentativesPerState, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfRepresentativesPerState Context triple: [United States Senate, hasNumberOfRepresentativesPerState, 2]
-
A.
numberOfRepresentatives
chosen
Indicates the quantity of representatives associated with a given entity or unit.
-
B.
numberOfStatesRepresented
Indicates how many distinct states are represented or covered in a given context or entity.
-
C.
numberOfColoniesRepresented
Indicates the count of distinct colonies that are represented or involved in relation to a given entity or context.
-
D.
haveUpperHouseRepresentationIn
Indicates that an entity holds or is assigned representation in a specified upper legislative chamber.
-
E.
representativeOfState
Indicates that an entity serves as an official representative or agent acting on behalf of a particular state or government.
- 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_69bd440f71348190b99938e59fb7f9a1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ff981fc819080d4466c6fe06cf3 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2e7b5c8190b8bf9d616dfa24f0 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:28 p.m.