Triple
T4845071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LEED v4 |
E108267
|
entity |
| Predicate | hasRatingLevel |
P59739
|
FINISHED |
| Object | Certified |
—
|
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: Certified | Statement: [LEED v4, hasRatingLevel, Certified]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRatingLevel Context triple: [LEED v4, hasRatingLevel, Certified]
-
A.
hasHighRatingOn
Indicates that one entity is evaluated or reviewed on another entity’s platform or system with a rating that meets or exceeds a defined high threshold.
-
B.
USRating
Indicates that an entity has been assigned a rating, classification, or evaluation according to a United States–based standard or system.
-
C.
aidRating
Indicates the assessed level or quality of assistance or support provided in a given context.
-
D.
ratingContext
Indicates the situational or contextual factors under which a rating is given or applies.
-
E.
hasContentRating
Indicates that something is associated with a specified content rating that reflects its suitability for particular audiences.
- 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_69bd4409b264819085ab855f3eb5381a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6e01872c81909607010c10538ad1 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2375a4819098e16acb982c8fab |
completed | March 20, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69bd6dfff1488190a32bbb615bfab970 |
completed | March 20, 2026, 3:55 p.m. |
Created at: March 20, 2026, 1:25 p.m.