Triple
T3876642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Westlake/MacArthur Park station |
E92516
|
entity |
| Predicate | isADACompliant |
P52091
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Westlake/MacArthur Park station, isADACompliant, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isADACompliant Context triple: [Westlake/MacArthur Park station, isADACompliant, yes]
-
A.
hasARIAcertification
Indicates that an entity possesses an ARIA (Accessible Rich Internet Applications) certification attesting to compliance with relevant accessibility standards.
-
B.
indicatesComplianceWith
Indicates that one entity conforms to, satisfies, or adheres to the rules, standards, or requirements specified by another entity or framework.
-
C.
providesCompliance
Indicates that one entity supplies or ensures adherence to required rules, standards, or regulations for another entity.
-
D.
hasSafetyRegulationCompliance
Indicates that an entity adheres to, satisfies, or is in conformity with specified safety regulations or standards.
-
E.
isSuitableFor
Indicates that one entity is appropriate, fitting, or well-matched for use, application, or association with 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_69aed967448c819086c4b358d37b25aa |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee7574c408190893e70bf80514838 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aef14f9bb4819098e64b527b546d74 |
completed | March 9, 2026, 4:11 p.m. |
Created at: March 9, 2026, 3:20 p.m.