Triple
T1413983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Storrow Drive |
E31868
|
entity |
| Predicate | isFrequently |
P26668
|
FINISHED |
| Object | congested during rush hour |
—
|
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: congested during rush hour | Statement: [Storrow Drive, isFrequently, congested during rush hour]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isFrequently Context triple: [Storrow Drive, isFrequently, congested during rush hour]
-
A.
isFrequentlyRecorded
Indicates that an entity is captured or documented many times within a given dataset, medium, or context.
-
B.
usesFrequency
Indicates that one entity employs or operates another entity at a specified rate, interval, or number of occurrences over time.
-
C.
isFrequentlyAdapted
Indicates that a work or source material is often transformed or re-created into new formats or versions, such as films, plays, or other media.
-
D.
frequentlyVisitedBy
Indicates that an entity is regularly or often visited by another entity.
-
E.
performedFrequency
Indicates how often an action or activity is carried out within a given time period.
- 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_69a49919a994819086528951bc224775 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c3e476f08190aed1576805c62462 |
completed | March 1, 2026, 10:55 p.m. |
| PD | Predicate disambiguation | batch_69a4bf048b648190ab77d9b45cb4855f |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4bf8158ac8190b8360ecccc2980bc |
completed | March 1, 2026, 10:36 p.m. |
Created at: March 1, 2026, 7:59 p.m.