Triple
T214647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2009 Red Line collision |
E4791
|
entity |
| Predicate | safetyRecommendationSource |
P488
|
FINISHED |
| Object | NTSB safety recommendations to WMATA |
—
|
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: NTSB safety recommendations to WMATA | Statement: [2009 Red Line collision, safetyRecommendationSource, NTSB safety recommendations to WMATA]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyRecommendationSource Context triple: [2009 Red Line collision, safetyRecommendationSource, NTSB safety recommendations to WMATA]
-
A.
canRecommend
Indicates that one entity is able or authorized to suggest or endorse another entity as suitable or preferable.
-
B.
implementsRecommendationOf
Indicates that one entity carries out or puts into practice a recommendation that was proposed or issued by another entity.
-
C.
recommendation
Indicates that one entity suggests, endorses, or advises another entity as suitable or beneficial for a particular purpose or context.
-
D.
recommendedAction
Indicates that one entity suggests or prescribes a particular action for another entity to take.
-
E.
advises
chosen
Indicates that one entity provides guidance, recommendations, or counsel to 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_69a2575cb1dc8190a01ad332426dc339 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25dcd2b208190855d5d8d70a3acfc |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b52190481908f299d26122bafd2 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:52 a.m.