Triple
T357483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York's 28th congressional district |
E7575
|
entity |
| Predicate | representedLevel |
P12271
|
FINISHED |
| Object | federal legislative |
—
|
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: federal legislative | Statement: [New York's 28th congressional district, representedLevel, federal legislative]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: representedLevel Context triple: [New York's 28th congressional district, representedLevel, federal legislative]
-
A.
classificationLevel
Indicates the degree or tier within an ordered system or hierarchy to which something is assigned for categorization or control purposes.
-
B.
meetsAtLevel
Indicates that two or more entities encounter or interact with each other at a specific hierarchical, structural, or progression level.
-
C.
revenueLevel
Indicates the relative amount or tier of revenue associated with an entity or activity.
-
D.
honorLevel
Indicates the degree or status of respect, distinction, or recognition accorded to an entity relative to others.
-
E.
representedLocallyBy
Indicates that an entity is expressed, implemented, or instantiated in a specific local form or representation by another entity.
- 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_69a2e7e696948190bebc966535995e45 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebb0e348819086e3ccd96c7b129e |
completed | Feb. 28, 2026, 1:20 p.m. |
| PD | Predicate disambiguation | batch_69a2e959ce948190a201c017eecb7c95 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea2c44408190946267525c88e811 |
completed | Feb. 28, 2026, 1:14 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.