Triple
T2017966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coat of arms of Yemen |
E44038
|
entity |
| Predicate | coffeePlantSymbolism |
P7837
|
FINISHED |
| Object | historical coffee production |
—
|
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: historical coffee production | Statement: [Coat of arms of Yemen, coffeePlantSymbolism, historical coffee production]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coffeePlantSymbolism Context triple: [Coat of arms of Yemen, coffeePlantSymbolism, historical coffee production]
-
A.
hasPlantSymbol
chosen
Indicates that an entity is associated with or represented by a particular plant as its symbolic emblem or sign.
-
B.
involvesPlant
Indicates that the relationship or action includes or pertains to a plant as a participating entity.
-
C.
isPlantOf
Indicates that one entity is a plant that belongs to, is associated with, or is characteristic of another entity (such as a region, habitat, or owner).
-
D.
plantType
Indicates the specific kind or category of plant that an entity is classified as.
-
E.
flowerSymbolMeaning
Indicates that a particular flower is used to represent or convey a specific symbolic meaning or message.
- 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_69a8891201bc8190aca837be6de41579 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb8ce71788190ac21beff10b08122 |
completed | March 7, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_69abb7a389408190a84a54856352f15b |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:38 p.m.