Triple
T12131645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nicotiana tabacum |
E288946
|
entity |
| Predicate | plantPartHarvested |
P51054
|
FINISHED |
| Object | leaves |
—
|
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: leaves | Statement: [Nicotiana tabacum, plantPartHarvested, leaves]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: plantPartHarvested Context triple: [Nicotiana tabacum, plantPartHarvested, leaves]
-
A.
hasPlantPart
chosen
Indicates that one entity includes, contains, or is composed of a specific plant part of another entity.
-
B.
ediblePart
Indicates that one entity is a part of another entity that can be eaten or consumed.
-
C.
cultivatedFor
Indicates that one entity is intentionally grown, raised, or developed for the benefit, use, or purpose of another entity.
-
D.
affectsPlantPart
Indicates that one entity produces an influence, change, or impact on a specific part of a plant.
-
E.
agriculturalProduce
Indicates that one entity is an agricultural product (such as crops or livestock-derived goods) produced by or associated with another entity.
- 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_69d6ab4b5e4c81909950b17151eb0951 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d91841615c819097f20a7447a1b8f4 |
completed | April 10, 2026, 3:33 p.m. |
| PD | Predicate disambiguation | batch_69d91508f8008190b3a90ec0bf0953ca |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:49 p.m.