Triple
T1983787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hunt Valley, Maryland |
E43090
|
entity |
| Predicate | hasOfficeParks |
P16026
|
FINISHED |
| Object | Cranbrook business parks |
—
|
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: Cranbrook business parks | Statement: [Hunt Valley, Maryland, hasOfficeParks, Cranbrook business parks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOfficeParks Context triple: [Hunt Valley, Maryland, hasOfficeParks, Cranbrook business parks]
-
A.
hasParks
Indicates that one entity possesses, contains, or is associated with one or more parks.
-
B.
hasBusinessPark
chosen
Indicates that one entity possesses, contains, or is associated with a business park as part of its facilities or properties.
-
C.
hasParkArea
Indicates that an entity includes or is associated with a designated park or recreational area within its boundaries.
-
D.
hasParkDistrict
Indicates that an entity is associated with, located within, or administered by a specific park district.
-
E.
hasIndustrialPark
Indicates that a location or entity possesses or contains an industrial park within its area or jurisdiction.
- 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_69a88713ddc88190a969715658ebe7a8 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb96f932881908bebfc4176fda7c0 |
completed | March 7, 2026, 5:36 a.m. |
| PD | Predicate disambiguation | batch_69abb798d288819083132cf14605bd02 |
completed | March 7, 2026, 5:28 a.m. |
Created at: March 4, 2026, 7:37 p.m.