Triple
T25365064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naju |
E636077
|
entity |
| Predicate | hasAgriculturalBrand |
P158239
|
FINISHED |
| Object | Naju pear brand |
—
|
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: Naju pear brand | Statement: [Naju, hasAgriculturalBrand, Naju pear brand]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAgriculturalBrand Context triple: [Naju, hasAgriculturalBrand, Naju pear brand]
-
A.
agricultureDivisionBrand
Indicates that a brand operates as part of, or is associated with, an agriculture-focused division within a larger organization.
-
B.
hasAgriculturalCharacter
Indicates that something possesses qualities, features, or uses typical of agriculture or farming activities.
-
C.
hasAgriculturalModel
Indicates that one entity possesses, uses, or is associated with a specific agricultural model (such as a framework, simulation, or methodology for agricultural processes).
-
D.
hasAgriculturalType
Indicates that an entity is associated with or classified by a specific type or category of agriculture.
-
E.
hasAgriculturalAssociation
Indicates that there exists a formal or recognized connection between an entity and an agricultural organization, group, or 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_69e75a9b7cf481909f2dcdfb37d95ca7 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f4a10ce1a8819081abc0012ddfaee7 |
completed | May 1, 2026, 12:48 p.m. |
| PD | Predicate disambiguation | batch_69f45d0dbc8c8190beecce679fce90a4 |
completed | May 1, 2026, 7:58 a.m. |
| PDg | Predicate description generation | batch_69f464ae42e88190b3549fdf4e0b425e |
completed | May 1, 2026, 8:30 a.m. |
Created at: April 21, 2026, 1:36 p.m.