Triple
T494493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Do-Nothing Congress |
E10260
|
entity |
| Predicate | appliedToInstitutionType |
P303
|
FINISHED |
| Object | bicameral legislature |
—
|
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: bicameral legislature | Statement: [Do-Nothing Congress, appliedToInstitutionType, bicameral legislature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliedToInstitutionType Context triple: [Do-Nothing Congress, appliedToInstitutionType, bicameral legislature]
-
A.
usedByInstitutionType
Indicates that something (such as a resource, tool, or service) is utilized or employed by a particular type or category of institution.
-
B.
eligibleInstitution
Indicates that an institution satisfies specified criteria or requirements to qualify for a particular program, benefit, or status.
-
C.
associatedWithInstitution
Indicates that an entity has a formal or recognized connection or affiliation with an institution.
-
D.
typeOfInstitution
chosen
Indicates the specific kind or category of institution that an entity belongs to or is classified as.
-
E.
servesInstitution
Indicates that one entity provides services or functions in support of a particular institution.
- 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_69a2e847df8481909239ec08ccf1e376 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f0fdd5608190815fa36485df8962 |
completed | Feb. 28, 2026, 1:43 p.m. |
| PD | Predicate disambiguation | batch_69a2edf90ca88190b6a182e5b6733612 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.