Triple
T1982790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Assembly Floor Analysis Unit |
E43065
|
entity |
| Predicate | usesInformationFrom |
P11520
|
FINISHED |
| Object | introduced bills |
—
|
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: introduced bills | Statement: [Assembly Floor Analysis Unit, usesInformationFrom, introduced bills]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesInformationFrom Context triple: [Assembly Floor Analysis Unit, usesInformationFrom, introduced bills]
-
A.
usesInformationSources
Indicates that an entity relies on or consults specified information sources to perform actions, make decisions, or obtain knowledge.
-
B.
providesInformationIn
Indicates that one entity supplies or conveys information within or through another entity or context.
-
C.
usesKnowledgeOf
Indicates that one entity applies or draws upon the knowledge possessed by another entity in performing an action or achieving a result.
-
D.
usedOn
Indicates that one entity is applied to, operated on, or otherwise utilized in relation to another entity.
-
E.
usedDataFrom
chosen
Indicates that one entity utilized or relied on data originating from another entity.
- 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_69a88713ddc88190a969715658ebe7a8 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb96f932881908bebfc4176fda7c0 |
completed | March 7, 2026, 5:36 a.m. |
| PD | Predicate disambiguation | batch_69abb798d288819083132cf14605bd02 |
completed | March 7, 2026, 5:28 a.m. |
Created at: March 4, 2026, 7:37 p.m.