Triple
T21214579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coat of arms of West Virginia |
E522801
|
entity |
| Predicate | cornstalksRepresent |
P39791
|
FINISHED |
| Object | agricultural abundance |
—
|
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: agricultural abundance | Statement: [Coat of arms of West Virginia, cornstalksRepresent, agricultural abundance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cornstalksRepresent Context triple: [Coat of arms of West Virginia, cornstalksRepresent, agricultural abundance]
-
A.
representsAgriculture
chosen
Indicates that one entity serves as an example, instance, or embodiment of agriculture in relation to another entity.
-
B.
seedRepresents
Indicates that one entity serves as a symbolic, conceptual, or prototypical representation of another, like a "seed" example standing in for a broader idea or set.
-
C.
numberOfRiceStalks
Indicates the quantity or count of rice stalks associated with a given entity or context.
-
D.
wheatRepresents
Indicates that one entity serves as a symbolic or representative stand-in for wheat in some context.
-
E.
majorCrop
Indicates that a particular crop is one of the primary or most important crops cultivated in a given area or context.
- 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_69e0b511ed84819099b449b4a111085c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e734727a30819089c433e4fe6f438a |
completed | April 21, 2026, 8:25 a.m. |
| PD | Predicate disambiguation | batch_69e5f6094e3c81909ee9699e00d371f7 |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3:39 p.m.