Triple
T29384672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | coat of arms of Niger |
E745218
|
entity |
| Predicate | agriculturalSymbol |
P39791
|
FINISHED |
| Object | millet |
—
|
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: millet | Statement: [coat of arms of Niger, agriculturalSymbol, millet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: agriculturalSymbol Context triple: [coat of arms of Niger, agriculturalSymbol, millet]
-
A.
representsAgriculture
chosen
Indicates that one entity serves as an example, instance, or embodiment of agriculture in relation to another entity.
-
B.
agriculturalFocus
Indicates that an entity is primarily concerned with, oriented toward, or specializing in agriculture or farming-related activities.
-
C.
agricultureUse
Indicates that something is used for, involved in, or designated for agricultural activities or purposes.
-
D.
agriculturalRole
Indicates a role or function that an entity has within agricultural activities, production, or systems.
-
E.
hasAgriculturalCharacter
Indicates that something possesses qualities, features, or uses typical of agriculture or farming activities.
- 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_69f0a79cfd5481909b4dde750cb8d2c6 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f669d0c45c8190ac5b67a0e89e8aae |
completed | May 2, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69f660f4f7a88190b93c60d76b86c912 |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 28, 2026, 2:37 p.m.