Triple
T4322900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matilija poppies |
E96558
|
entity |
| Predicate | maintenanceNote |
P56231
|
FINISHED |
| Object | can spread aggressively via rhizomes |
—
|
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: can spread aggressively via rhizomes | Statement: [Matilija poppies, maintenanceNote, can spread aggressively via rhizomes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maintenanceNote Context triple: [Matilija poppies, maintenanceNote, can spread aggressively via rhizomes]
-
A.
maintenance
Indicates that an entity performs, requires, or is involved in upkeep, repair, or preservation activities for another entity or system.
-
B.
maintenanceFeature
Indicates that one entity serves as a maintenance-related feature, capability, or component associated with another entity.
-
C.
maintenanceConcept
Indicates a conceptual or abstract relationship related to maintenance activities, strategies, or principles rather than a specific maintenance event.
-
D.
maintenancePractice
Indicates the specific actions or methods used to preserve, repair, or optimize the condition or performance of something over time.
-
E.
crewNote
Indicates that a note or comment is recorded about a crew member or crew-related activity.
- 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_69b345422aac81909ddbadae437d122e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b351177eb88190b89fa49a88add5e8 |
completed | March 12, 2026, 11:49 p.m. |
| PD | Predicate disambiguation | batch_69b34f4bec888190987fc2631498b637 |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b3501834448190bedf775a80da4778 |
completed | March 12, 2026, 11:45 p.m. |
Created at: March 12, 2026, 11:12 p.m.