Triple
T7586522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suitland Parkway (NPS-managed segments) |
E179624
|
entity |
| Predicate | hasMaintenanceGoal |
P78004
|
FINISHED |
| Object | protect scenic views |
—
|
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: protect scenic views | Statement: [Suitland Parkway (NPS-managed segments), hasMaintenanceGoal, protect scenic views]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaintenanceGoal Context triple: [Suitland Parkway (NPS-managed segments), hasMaintenanceGoal, protect scenic views]
-
A.
hasManagementGoal
Indicates that an entity is associated with a specific management objective or target it is intended to achieve or support.
-
B.
hasOperationalGoal
Indicates that an entity is associated with a specific objective or target it aims to achieve through its operations or activities.
-
C.
hasPlanningGoal
Indicates that an entity is associated with, or directed toward achieving, a specific planning objective or target state.
-
D.
hasMaintenance
Indicates that an entity is subject to, associated with, or requires a particular maintenance activity or maintenance record.
-
E.
hasPrimaryGoal
Indicates that an entity’s main or most important objective is the specified goal.
- F. None of above. chosen
Provenance (4 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_69c69f335248819093c1006f30513708 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f9970efc8190b1b9286d86331359 |
completed | March 27, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e04c2c8190a889d928515d9b8e |
completed | March 27, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69c6f8184bb08190b2f70545a6aa277c |
completed | March 27, 2026, 9:35 p.m. |
Created at: March 27, 2026, 3:52 p.m.