Triple
T3766830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Community Reinvestment Act |
E82697
|
entity |
| Predicate | possibleRating |
P27677
|
FINISHED |
| Object | Outstanding |
—
|
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: Outstanding | Statement: [Community Reinvestment Act, possibleRating, Outstanding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: possibleRating Context triple: [Community Reinvestment Act, possibleRating, Outstanding]
-
A.
rating
Indicates an evaluation relationship where one entity assigns a qualitative or quantitative score or judgment to another entity.
-
B.
ratingExpectation
chosen
Indicates an anticipated or predicted evaluation score that one entity expects another entity to receive or assign.
-
C.
ratingContext
Indicates the situational or contextual factors under which a rating is given or applies.
-
D.
aidRating
Indicates the assessed level or quality of assistance or support provided in a given context.
-
E.
ratingDescription
Indicates the textual explanation or qualitative summary associated with a given rating or score.
- 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_69ad8b207b0081909d2b48843fbd8795 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcc0004608190a810ae0270ae2478 |
completed | March 8, 2026, 7:20 p.m. |
| PD | Predicate disambiguation | batch_69adc04ec36c8190bd5b944d4f4d32aa |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:35 p.m.