Triple
T9402424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dwight Schrute |
E226504
|
entity |
| Predicate | farmProduct |
P75269
|
FINISHED |
| Object | beets |
—
|
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: beets | Statement: [Dwight Schrute, farmProduct, beets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: farmProduct Context triple: [Dwight Schrute, farmProduct, beets]
-
A.
agriculturalProduce
chosen
Indicates that one entity is an agricultural product (such as crops or livestock-derived goods) produced by or associated with another entity.
-
B.
traditionalAgriculturalProduct
Indicates that something is recognized as an agricultural product produced using long-established, customary methods and practices.
-
C.
typeOfFarmProductInDispute
Indicates that a specific kind of farm product is the subject of a disagreement, conflict, or legal dispute between parties.
-
D.
crop
Indicates the action of cutting or trimming part of an object or image, typically to remove unwanted outer areas while keeping a selected region.
-
E.
cultivatedFor
Indicates that one entity is intentionally grown, raised, or developed for the benefit, use, or purpose of 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_69ca843170f88190800a8ab2b5fc568e |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd51be35cc8190bafad423a142c305 |
completed | April 1, 2026, 5:11 p.m. |
| PD | Predicate disambiguation | batch_69cca545b2448190a4297312e39c21ac |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:46 p.m.