Triple
T23929426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nine Mile Run greenway |
E602449
|
entity |
| Predicate | hasRecreationGoal |
P69054
|
FINISHED |
| Object | providing urban outdoor recreation |
—
|
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: providing urban outdoor recreation | Statement: [Nine Mile Run greenway, hasRecreationGoal, providing urban outdoor recreation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRecreationGoal Context triple: [Nine Mile Run greenway, hasRecreationGoal, providing urban outdoor recreation]
-
A.
hasRecreationPurpose
Indicates that something is used or intended to be used for recreational or leisure activities.
-
B.
recreationManagementGoal
Indicates a management objective or intended outcome related to how recreational activities are planned, controlled, or guided.
-
C.
hasRecreationActivity
Indicates that an entity provides, includes, or is associated with a particular recreational activity.
-
D.
hasRecreationValue
Indicates that something provides opportunities or benefits for leisure, enjoyment, or recreational activities.
-
E.
hasPlanningGoal
chosen
Indicates that an entity is associated with, or directed toward achieving, a specific planning objective or target state.
- 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_69e2953b928c819095395fa87baca583 |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1cf9a18248190b20991969921ecfd |
completed | April 29, 2026, 9:30 a.m. |
| PD | Predicate disambiguation | batch_69f16151ebdc819086e9e1d7cc1f4f3c |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:55 p.m.