Triple
T7869168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Midlothian Meadows Forest Preserve |
E182694
|
entity |
| Predicate | hasLandUseDesignation |
P43475
|
FINISHED |
| Object | forest preserve |
—
|
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: forest preserve | Statement: [Midlothian Meadows Forest Preserve, hasLandUseDesignation, forest preserve]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandUseDesignation Context triple: [Midlothian Meadows Forest Preserve, hasLandUseDesignation, forest preserve]
-
A.
hasLandUseCharacter
chosen
Indicates that one entity possesses or is associated with a particular type or pattern of land use.
-
B.
cityPlanningDesignation
Indicates how an area is officially classified or designated within urban or municipal planning (e.g., residential, commercial, industrial).
-
C.
hasRegionDesignation
Indicates that an entity is assigned or associated with a specific regional classification or designation.
-
D.
landUseIncludes
Indicates that a specified land area contains or permits the specified type(s) of land use within its boundaries.
-
E.
landGrantDesignation
Indicates that an institution has been formally designated as a land-grant institution under a land-grant program or legislation.
- 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_69ca82894d9081908a832bfce71a4714 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3848d6d88190830afcf04ad12154 |
completed | March 31, 2026, 2:58 a.m. |
| PD | Predicate disambiguation | batch_69cae925ca388190ae4a01fa76e957e8 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:55 p.m.