Triple
T27104060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Woods landscape design |
E686515
|
entity |
| Predicate | hasMaintenanceConcern |
P122338
|
FINISHED |
| Object | erosion control |
—
|
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: erosion control | Statement: [North Woods landscape design, hasMaintenanceConcern, erosion control]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaintenanceConcern Context triple: [North Woods landscape design, hasMaintenanceConcern, erosion control]
-
A.
hasMaintenance
Indicates that an entity is subject to, associated with, or requires a particular maintenance activity or maintenance record.
-
B.
hasManagementConcern
Indicates that one entity has responsibility, authority, or involvement in overseeing, directing, or managing another entity or activity.
-
C.
hasMaintenanceService
Indicates that an entity receives or is covered by a maintenance service provided by another entity.
-
D.
hasMaintenanceType
Indicates the specific category or kind of maintenance associated with an asset, component, or maintenance event.
-
E.
hasInfrastructureConcern
chosen
Indicates that an entity has a problem, risk, or issue related to infrastructure that requires attention or management.
- 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_69ef148accd48190b6ed6e13a15f2a4f |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69fdbc5ef46c8190bbcfb9798f4615b7 |
completed | May 8, 2026, 10:35 a.m. |
| PD | Predicate disambiguation | batch_69fdbb270338819082ce3f73903e884f |
completed | May 8, 2026, 10:29 a.m. |
Created at: April 27, 2026, 8:49 a.m.