Triple
T37483987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brier |
E931479
|
entity |
| Predicate | averageCommuteDestination |
P89542
|
FINISHED |
| Object | Seattle |
—
|
NE NERFINISHED |
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: Seattle | Statement: [Brier, averageCommuteDestination, Seattle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageCommuteDestination Context triple: [Brier, averageCommuteDestination, Seattle]
-
A.
commuterDestination
Indicates that a location serves as the endpoint or target place to which a person regularly travels for commuting.
-
B.
typicalDestinationMetroArea
chosen
Indicates the metro area that is most commonly the destination associated with a given origin or context.
-
C.
commutesBetween
Indicates a regular pattern of travel back and forth between two locations, typically for work, study, or routine activities.
-
D.
commuterRoute
Indicates a route that is regularly used by people traveling between home and work or other routine daily destinations.
-
E.
commuterHubFor
Indicates a location that serves as a primary transit or gathering point for commuters traveling to or from another place.
- 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_69f76ec382248190b47844df596123c6 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbacaf54648190811ea33b34907e8e |
completed | May 6, 2026, 9:03 p.m. |
| PD | Predicate disambiguation | batch_69fba883f770819091059c6f6c6af9f7 |
completed | May 6, 2026, 8:45 p.m. |
Created at: May 3, 2026, 4:17 p.m.