Triple
T33036852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White Marsh, Maryland |
E845338
|
entity |
| Predicate | shoppingDestinationFor |
P47325
|
FINISHED |
| Object | Baltimore County residents |
—
|
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: Baltimore County residents | Statement: [White Marsh, Maryland, shoppingDestinationFor, Baltimore County residents]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shoppingDestinationFor Context triple: [White Marsh, Maryland, shoppingDestinationFor, Baltimore County residents]
-
A.
shoppingAccess
Indicates that an entity has the ability or opportunity to reach and use shopping facilities or retail services.
-
B.
shoppingFeature
Indicates that an entity provides or supports a shopping-related capability, option, or functionality for another entity.
-
C.
isShoppingDestination
chosen
Indicates that a place serves as a primary location where people go to shop for goods or services.
-
D.
shoppingStyle
Indicates the manner or approach an entity typically uses when shopping, such as their preferred methods, habits, or decision-making style.
-
E.
shopSection
Indicates the specific section or area within a shop where an item, activity, or service is located or takes 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_69f34951348c8190b56746b0a7018182 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d6a6b04c8190bee4cf9c00665ef7 |
completed | May 3, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69f6d27120988190aacec621cf2bf0e8 |
completed | May 3, 2026, 4:43 a.m. |
Created at: May 1, 2026, 1:24 a.m.